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Final model checkpoint

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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: Qwen/Qwen2.5-0.5B
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: tfa_output_2025_m02_d07_t07h_45m_38s
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # tfa_output_2025_m02_d07_t07h_45m_38s
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+
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+ This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.1965
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-06
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+ - train_batch_size: 2
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 8
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+ - optimizer: Use OptimizerNames.PAGED_ADAMW with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: constant_with_warmup
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+ - lr_scheduler_warmup_ratio: 0.05
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+ - num_epochs: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | No log | 0 | 0 | 1.3072 |
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+ | 4.0374 | 0.0030 | 1 | 1.3072 |
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+ | 3.7206 | 0.0060 | 2 | 1.3073 |
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+ | 3.6304 | 0.0090 | 3 | 1.3075 |
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+ | 3.9205 | 0.0119 | 4 | 1.3072 |
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+ | 3.8914 | 0.0149 | 5 | 1.3074 |
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+ | 3.7914 | 0.0179 | 6 | 1.3071 |
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+ | 3.6888 | 0.0209 | 7 | 1.3073 |
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+ | 3.9573 | 0.0239 | 8 | 1.3068 |
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+ | 3.9216 | 0.0269 | 9 | 1.3068 |
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+ | 3.8295 | 0.0299 | 10 | 1.3065 |
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+ | 3.7775 | 0.0328 | 11 | 1.3061 |
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+ | 4.1608 | 0.0358 | 12 | 1.3056 |
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+ | 3.8315 | 0.0388 | 13 | 1.3047 |
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+ | 3.8961 | 0.0418 | 14 | 1.3041 |
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+ | 3.5064 | 0.0448 | 15 | 1.3034 |
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+ | 3.8623 | 0.0478 | 16 | 1.3029 |
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+ | 3.7882 | 0.0507 | 17 | 1.3022 |
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+ | 3.9906 | 0.0537 | 18 | 1.3004 |
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+ | 3.8721 | 0.0567 | 19 | 1.2990 |
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+ | 3.8715 | 0.0597 | 20 | 1.2982 |
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+ | 3.7604 | 0.0627 | 21 | 1.2970 |
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+ | 3.7259 | 0.0657 | 22 | 1.2961 |
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+ | 3.769 | 0.0687 | 23 | 1.2948 |
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+ | 3.9388 | 0.0716 | 24 | 1.2935 |
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+ | 3.8075 | 0.0746 | 25 | 1.2921 |
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+ | 3.9561 | 0.0776 | 26 | 1.2913 |
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+ | 3.8021 | 0.0806 | 27 | 1.2904 |
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+ | 3.658 | 0.0836 | 28 | 1.2892 |
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+ | 3.7469 | 0.0866 | 29 | 1.2883 |
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+ | 3.9257 | 0.0896 | 30 | 1.2873 |
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+ | 3.7349 | 0.0925 | 31 | 1.2864 |
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+ | 3.7425 | 0.0955 | 32 | 1.2854 |
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+ | 3.3611 | 0.0985 | 33 | 1.2843 |
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+ | 3.5493 | 0.1015 | 34 | 1.2833 |
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+ | 3.596 | 0.1045 | 35 | 1.2828 |
89
+ | 3.8972 | 0.1075 | 36 | 1.2816 |
90
+ | 3.9669 | 0.1104 | 37 | 1.2808 |
91
+ | 4.0005 | 0.1134 | 38 | 1.2800 |
92
+ | 3.6185 | 0.1164 | 39 | 1.2785 |
93
+ | 4.0852 | 0.1194 | 40 | 1.2776 |
94
+ | 3.452 | 0.1224 | 41 | 1.2769 |
95
+ | 4.017 | 0.1254 | 42 | 1.2761 |
96
+ | 3.8406 | 0.1284 | 43 | 1.2753 |
97
+ | 3.5601 | 0.1313 | 44 | 1.2746 |
98
+ | 3.7764 | 0.1343 | 45 | 1.2731 |
99
+ | 3.8586 | 0.1373 | 46 | 1.2722 |
100
+ | 3.2432 | 0.1403 | 47 | 1.2715 |
101
+ | 3.5002 | 0.1433 | 48 | 1.2706 |
102
+ | 3.4933 | 0.1463 | 49 | 1.2701 |
103
+ | 3.5798 | 0.1493 | 50 | 1.2688 |
104
+ | 3.6943 | 0.1522 | 51 | 1.2681 |
105
+ | 3.3713 | 0.1552 | 52 | 1.2675 |
106
+ | 3.6274 | 0.1582 | 53 | 1.2666 |
107
+ | 3.5537 | 0.1612 | 54 | 1.2653 |
108
+ | 3.5242 | 0.1642 | 55 | 1.2646 |
109
+ | 3.6243 | 0.1672 | 56 | 1.2637 |
110
+ | 3.4449 | 0.1701 | 57 | 1.2630 |
111
+ | 3.6649 | 0.1731 | 58 | 1.2621 |
112
+ | 3.643 | 0.1761 | 59 | 1.2615 |
113
+ | 3.5039 | 0.1791 | 60 | 1.2607 |
114
+ | 3.7135 | 0.1821 | 61 | 1.2595 |
115
+ | 3.8718 | 0.1851 | 62 | 1.2587 |
116
+ | 3.4509 | 0.1881 | 63 | 1.2581 |
117
+ | 3.7153 | 0.1910 | 64 | 1.2569 |
118
+ | 3.6279 | 0.1940 | 65 | 1.2564 |
119
+ | 3.1831 | 0.1970 | 66 | 1.2557 |
120
+ | 3.6647 | 0.2 | 67 | 1.2548 |
121
+ | 3.8362 | 0.2030 | 68 | 1.2543 |
122
+ | 3.7985 | 0.2060 | 69 | 1.2533 |
123
+ | 3.6422 | 0.2090 | 70 | 1.2525 |
124
+ | 3.4649 | 0.2119 | 71 | 1.2522 |
125
+ | 3.645 | 0.2149 | 72 | 1.2518 |
126
+ | 3.6387 | 0.2179 | 73 | 1.2508 |
127
+ | 3.6069 | 0.2209 | 74 | 1.2500 |
128
+ | 3.297 | 0.2239 | 75 | 1.2492 |
129
+ | 3.2928 | 0.2269 | 76 | 1.2487 |
130
+ | 3.4727 | 0.2299 | 77 | 1.2482 |
131
+ | 3.2704 | 0.2328 | 78 | 1.2473 |
132
+ | 3.4458 | 0.2358 | 79 | 1.2467 |
133
+ | 3.492 | 0.2388 | 80 | 1.2458 |
134
+ | 3.5288 | 0.2418 | 81 | 1.2453 |
135
+ | 3.6266 | 0.2448 | 82 | 1.2447 |
136
+ | 3.6181 | 0.2478 | 83 | 1.2442 |
137
+ | 3.4847 | 0.2507 | 84 | 1.2434 |
138
+ | 3.7349 | 0.2537 | 85 | 1.2431 |
139
+ | 3.7247 | 0.2567 | 86 | 1.2424 |
140
+ | 3.3359 | 0.2597 | 87 | 1.2419 |
141
+ | 3.3628 | 0.2627 | 88 | 1.2408 |
142
+ | 3.6579 | 0.2657 | 89 | 1.2408 |
143
+ | 3.601 | 0.2687 | 90 | 1.2406 |
144
+ | 3.1941 | 0.2716 | 91 | 1.2399 |
145
+ | 3.5671 | 0.2746 | 92 | 1.2395 |
146
+ | 3.7115 | 0.2776 | 93 | 1.2385 |
147
+ | 3.532 | 0.2806 | 94 | 1.2381 |
148
+ | 3.5191 | 0.2836 | 95 | 1.2374 |
149
+ | 3.6731 | 0.2866 | 96 | 1.2371 |
150
+ | 3.7962 | 0.2896 | 97 | 1.2367 |
151
+ | 3.7644 | 0.2925 | 98 | 1.2361 |
152
+ | 3.4904 | 0.2955 | 99 | 1.2356 |
153
+ | 3.5935 | 0.2985 | 100 | 1.2354 |
154
+ | 3.577 | 0.3015 | 101 | 1.2346 |
155
+ | 3.693 | 0.3045 | 102 | 1.2344 |
156
+ | 3.6223 | 0.3075 | 103 | 1.2340 |
157
+ | 3.4485 | 0.3104 | 104 | 1.2334 |
158
+ | 3.4748 | 0.3134 | 105 | 1.2329 |
159
+ | 3.4188 | 0.3164 | 106 | 1.2324 |
160
+ | 3.5004 | 0.3194 | 107 | 1.2321 |
161
+ | 3.6142 | 0.3224 | 108 | 1.2317 |
162
+ | 3.3817 | 0.3254 | 109 | 1.2313 |
163
+ | 3.5531 | 0.3284 | 110 | 1.2311 |
164
+ | 3.1087 | 0.3313 | 111 | 1.2306 |
165
+ | 3.3683 | 0.3343 | 112 | 1.2304 |
166
+ | 3.8721 | 0.3373 | 113 | 1.2298 |
167
+ | 3.7024 | 0.3403 | 114 | 1.2293 |
168
+ | 3.5345 | 0.3433 | 115 | 1.2289 |
169
+ | 3.573 | 0.3463 | 116 | 1.2287 |
170
+ | 3.5846 | 0.3493 | 117 | 1.2284 |
171
+ | 3.5404 | 0.3522 | 118 | 1.2282 |
172
+ | 3.5606 | 0.3552 | 119 | 1.2280 |
173
+ | 3.5055 | 0.3582 | 120 | 1.2274 |
174
+ | 3.4956 | 0.3612 | 121 | 1.2270 |
175
+ | 3.608 | 0.3642 | 122 | 1.2268 |
176
+ | 3.2361 | 0.3672 | 123 | 1.2265 |
177
+ | 3.488 | 0.3701 | 124 | 1.2265 |
178
+ | 3.2155 | 0.3731 | 125 | 1.2260 |
179
+ | 3.3639 | 0.3761 | 126 | 1.2256 |
180
+ | 3.3634 | 0.3791 | 127 | 1.2256 |
181
+ | 3.4846 | 0.3821 | 128 | 1.2254 |
182
+ | 3.5508 | 0.3851 | 129 | 1.2252 |
183
+ | 3.5719 | 0.3881 | 130 | 1.2246 |
184
+ | 3.3178 | 0.3910 | 131 | 1.2247 |
185
+ | 3.4262 | 0.3940 | 132 | 1.2243 |
186
+ | 3.4895 | 0.3970 | 133 | 1.2239 |
187
+ | 3.5872 | 0.4 | 134 | 1.2234 |
188
+ | 3.4766 | 0.4030 | 135 | 1.2233 |
189
+ | 3.3568 | 0.4060 | 136 | 1.2230 |
190
+ | 3.5747 | 0.4090 | 137 | 1.2230 |
191
+ | 2.9403 | 0.4119 | 138 | 1.2226 |
192
+ | 3.3463 | 0.4149 | 139 | 1.2223 |
193
+ | 3.3048 | 0.4179 | 140 | 1.2217 |
194
+ | 3.2987 | 0.4209 | 141 | 1.2218 |
195
+ | 3.4811 | 0.4239 | 142 | 1.2216 |
196
+ | 3.64 | 0.4269 | 143 | 1.2211 |
197
+ | 3.1703 | 0.4299 | 144 | 1.2206 |
198
+ | 3.2906 | 0.4328 | 145 | 1.2205 |
199
+ | 3.6134 | 0.4358 | 146 | 1.2199 |
200
+ | 3.348 | 0.4388 | 147 | 1.2197 |
201
+ | 3.2428 | 0.4418 | 148 | 1.2198 |
202
+ | 3.573 | 0.4448 | 149 | 1.2197 |
203
+ | 3.6921 | 0.4478 | 150 | 1.2191 |
204
+ | 3.5082 | 0.4507 | 151 | 1.2191 |
205
+ | 3.3445 | 0.4537 | 152 | 1.2189 |
206
+ | 3.3521 | 0.4567 | 153 | 1.2187 |
207
+ | 3.4538 | 0.4597 | 154 | 1.2183 |
208
+ | 3.3225 | 0.4627 | 155 | 1.2179 |
209
+ | 3.6838 | 0.4657 | 156 | 1.2179 |
210
+ | 3.3113 | 0.4687 | 157 | 1.2177 |
211
+ | 3.4141 | 0.4716 | 158 | 1.2175 |
212
+ | 2.8407 | 0.4746 | 159 | 1.2173 |
213
+ | 3.3262 | 0.4776 | 160 | 1.2168 |
214
+ | 3.6585 | 0.4806 | 161 | 1.2167 |
215
+ | 3.4489 | 0.4836 | 162 | 1.2166 |
216
+ | 3.6269 | 0.4866 | 163 | 1.2162 |
217
+ | 3.3826 | 0.4896 | 164 | 1.2160 |
218
+ | 3.4506 | 0.4925 | 165 | 1.2159 |
219
+ | 3.2749 | 0.4955 | 166 | 1.2151 |
220
+ | 3.7262 | 0.4985 | 167 | 1.2151 |
221
+ | 3.4615 | 0.5015 | 168 | 1.2147 |
222
+ | 3.5982 | 0.5045 | 169 | 1.2149 |
223
+ | 3.5301 | 0.5075 | 170 | 1.2142 |
224
+ | 3.1629 | 0.5104 | 171 | 1.2145 |
225
+ | 3.3415 | 0.5134 | 172 | 1.2140 |
226
+ | 3.2653 | 0.5164 | 173 | 1.2139 |
227
+ | 3.2757 | 0.5194 | 174 | 1.2137 |
228
+ | 3.3495 | 0.5224 | 175 | 1.2136 |
229
+ | 3.4542 | 0.5254 | 176 | 1.2135 |
230
+ | 3.5153 | 0.5284 | 177 | 1.2130 |
231
+ | 3.2836 | 0.5313 | 178 | 1.2126 |
232
+ | 3.2877 | 0.5343 | 179 | 1.2123 |
233
+ | 3.4662 | 0.5373 | 180 | 1.2125 |
234
+ | 3.0825 | 0.5403 | 181 | 1.2123 |
235
+ | 3.381 | 0.5433 | 182 | 1.2121 |
236
+ | 3.3843 | 0.5463 | 183 | 1.2118 |
237
+ | 3.0211 | 0.5493 | 184 | 1.2116 |
238
+ | 3.2045 | 0.5522 | 185 | 1.2113 |
239
+ | 3.515 | 0.5552 | 186 | 1.2111 |
240
+ | 3.3176 | 0.5582 | 187 | 1.2113 |
241
+ | 3.5145 | 0.5612 | 188 | 1.2109 |
242
+ | 3.135 | 0.5642 | 189 | 1.2106 |
243
+ | 3.5442 | 0.5672 | 190 | 1.2107 |
244
+ | 3.3991 | 0.5701 | 191 | 1.2106 |
245
+ | 3.2577 | 0.5731 | 192 | 1.2103 |
246
+ | 3.286 | 0.5761 | 193 | 1.2102 |
247
+ | 3.4492 | 0.5791 | 194 | 1.2097 |
248
+ | 3.7012 | 0.5821 | 195 | 1.2098 |
249
+ | 3.2023 | 0.5851 | 196 | 1.2097 |
250
+ | 3.207 | 0.5881 | 197 | 1.2097 |
251
+ | 3.3281 | 0.5910 | 198 | 1.2091 |
252
+ | 3.3071 | 0.5940 | 199 | 1.2091 |
253
+ | 3.39 | 0.5970 | 200 | 1.2091 |
254
+ | 3.2437 | 0.6 | 201 | 1.2090 |
255
+ | 3.2771 | 0.6030 | 202 | 1.2089 |
256
+ | 3.4758 | 0.6060 | 203 | 1.2085 |
257
+ | 3.2785 | 0.6090 | 204 | 1.2082 |
258
+ | 3.524 | 0.6119 | 205 | 1.2084 |
259
+ | 3.3163 | 0.6149 | 206 | 1.2082 |
260
+ | 3.3725 | 0.6179 | 207 | 1.2078 |
261
+ | 3.4803 | 0.6209 | 208 | 1.2078 |
262
+ | 3.1456 | 0.6239 | 209 | 1.2080 |
263
+ | 3.2719 | 0.6269 | 210 | 1.2079 |
264
+ | 3.4017 | 0.6299 | 211 | 1.2074 |
265
+ | 3.3843 | 0.6328 | 212 | 1.2073 |
266
+ | 3.5353 | 0.6358 | 213 | 1.2070 |
267
+ | 3.2673 | 0.6388 | 214 | 1.2072 |
268
+ | 3.2824 | 0.6418 | 215 | 1.2070 |
269
+ | 3.3562 | 0.6448 | 216 | 1.2069 |
270
+ | 3.1972 | 0.6478 | 217 | 1.2069 |
271
+ | 3.3425 | 0.6507 | 218 | 1.2067 |
272
+ | 3.1529 | 0.6537 | 219 | 1.2066 |
273
+ | 3.0392 | 0.6567 | 220 | 1.2062 |
274
+ | 2.9891 | 0.6597 | 221 | 1.2063 |
275
+ | 3.451 | 0.6627 | 222 | 1.2059 |
276
+ | 3.19 | 0.6657 | 223 | 1.2061 |
277
+ | 3.2682 | 0.6687 | 224 | 1.2057 |
278
+ | 3.4182 | 0.6716 | 225 | 1.2055 |
279
+ | 3.4638 | 0.6746 | 226 | 1.2054 |
280
+ | 3.2297 | 0.6776 | 227 | 1.2053 |
281
+ | 3.3207 | 0.6806 | 228 | 1.2051 |
282
+ | 3.2218 | 0.6836 | 229 | 1.2051 |
283
+ | 3.2048 | 0.6866 | 230 | 1.2049 |
284
+ | 3.1883 | 0.6896 | 231 | 1.2050 |
285
+ | 3.5168 | 0.6925 | 232 | 1.2048 |
286
+ | 3.4838 | 0.6955 | 233 | 1.2047 |
287
+ | 3.148 | 0.6985 | 234 | 1.2050 |
288
+ | 3.35 | 0.7015 | 235 | 1.2045 |
289
+ | 3.156 | 0.7045 | 236 | 1.2043 |
290
+ | 3.2269 | 0.7075 | 237 | 1.2045 |
291
+ | 3.1877 | 0.7104 | 238 | 1.2039 |
292
+ | 3.4361 | 0.7134 | 239 | 1.2041 |
293
+ | 3.2583 | 0.7164 | 240 | 1.2039 |
294
+ | 3.3384 | 0.7194 | 241 | 1.2037 |
295
+ | 3.235 | 0.7224 | 242 | 1.2038 |
296
+ | 3.2664 | 0.7254 | 243 | 1.2037 |
297
+ | 3.1289 | 0.7284 | 244 | 1.2033 |
298
+ | 3.4714 | 0.7313 | 245 | 1.2035 |
299
+ | 3.4815 | 0.7343 | 246 | 1.2035 |
300
+ | 3.5291 | 0.7373 | 247 | 1.2033 |
301
+ | 3.2485 | 0.7403 | 248 | 1.2032 |
302
+ | 3.3338 | 0.7433 | 249 | 1.2028 |
303
+ | 3.0806 | 0.7463 | 250 | 1.2030 |
304
+ | 3.3287 | 0.7493 | 251 | 1.2027 |
305
+ | 3.4036 | 0.7522 | 252 | 1.2025 |
306
+ | 3.2587 | 0.7552 | 253 | 1.2024 |
307
+ | 2.8553 | 0.7582 | 254 | 1.2025 |
308
+ | 3.3085 | 0.7612 | 255 | 1.2022 |
309
+ | 3.0679 | 0.7642 | 256 | 1.2023 |
310
+ | 3.2612 | 0.7672 | 257 | 1.2022 |
311
+ | 3.5312 | 0.7701 | 258 | 1.2021 |
312
+ | 3.2655 | 0.7731 | 259 | 1.2018 |
313
+ | 3.054 | 0.7761 | 260 | 1.2018 |
314
+ | 3.306 | 0.7791 | 261 | 1.2017 |
315
+ | 3.2836 | 0.7821 | 262 | 1.2015 |
316
+ | 2.992 | 0.7851 | 263 | 1.2014 |
317
+ | 3.2031 | 0.7881 | 264 | 1.2013 |
318
+ | 3.4771 | 0.7910 | 265 | 1.2013 |
319
+ | 3.2433 | 0.7940 | 266 | 1.2011 |
320
+ | 3.0587 | 0.7970 | 267 | 1.2012 |
321
+ | 3.0495 | 0.8 | 268 | 1.2012 |
322
+ | 3.3093 | 0.8030 | 269 | 1.2008 |
323
+ | 3.3915 | 0.8060 | 270 | 1.2010 |
324
+ | 3.345 | 0.8090 | 271 | 1.2008 |
325
+ | 3.1808 | 0.8119 | 272 | 1.2006 |
326
+ | 3.209 | 0.8149 | 273 | 1.2007 |
327
+ | 3.0482 | 0.8179 | 274 | 1.2004 |
328
+ | 2.9668 | 0.8209 | 275 | 1.2006 |
329
+ | 3.0532 | 0.8239 | 276 | 1.2008 |
330
+ | 3.3684 | 0.8269 | 277 | 1.2004 |
331
+ | 3.2661 | 0.8299 | 278 | 1.2003 |
332
+ | 3.0364 | 0.8328 | 279 | 1.2003 |
333
+ | 3.4541 | 0.8358 | 280 | 1.2002 |
334
+ | 3.3404 | 0.8388 | 281 | 1.2001 |
335
+ | 3.4284 | 0.8418 | 282 | 1.1999 |
336
+ | 3.4654 | 0.8448 | 283 | 1.1997 |
337
+ | 3.0229 | 0.8478 | 284 | 1.2000 |
338
+ | 3.2988 | 0.8507 | 285 | 1.1999 |
339
+ | 3.3894 | 0.8537 | 286 | 1.1995 |
340
+ | 3.2594 | 0.8567 | 287 | 1.1995 |
341
+ | 3.2245 | 0.8597 | 288 | 1.1995 |
342
+ | 3.0186 | 0.8627 | 289 | 1.1991 |
343
+ | 3.0315 | 0.8657 | 290 | 1.1990 |
344
+ | 2.8311 | 0.8687 | 291 | 1.1990 |
345
+ | 3.1816 | 0.8716 | 292 | 1.1988 |
346
+ | 3.3245 | 0.8746 | 293 | 1.1987 |
347
+ | 3.434 | 0.8776 | 294 | 1.1988 |
348
+ | 3.09 | 0.8806 | 295 | 1.1986 |
349
+ | 3.4151 | 0.8836 | 296 | 1.1983 |
350
+ | 3.2193 | 0.8866 | 297 | 1.1984 |
351
+ | 3.3492 | 0.8896 | 298 | 1.1985 |
352
+ | 3.1033 | 0.8925 | 299 | 1.1983 |
353
+ | 3.3869 | 0.8955 | 300 | 1.1984 |
354
+ | 3.2651 | 0.8985 | 301 | 1.1981 |
355
+ | 3.3921 | 0.9015 | 302 | 1.1981 |
356
+ | 3.3988 | 0.9045 | 303 | 1.1981 |
357
+ | 3.3168 | 0.9075 | 304 | 1.1983 |
358
+ | 3.173 | 0.9104 | 305 | 1.1980 |
359
+ | 3.1127 | 0.9134 | 306 | 1.1981 |
360
+ | 2.9588 | 0.9164 | 307 | 1.1979 |
361
+ | 3.1549 | 0.9194 | 308 | 1.1978 |
362
+ | 3.1344 | 0.9224 | 309 | 1.1978 |
363
+ | 3.0571 | 0.9254 | 310 | 1.1977 |
364
+ | 3.299 | 0.9284 | 311 | 1.1976 |
365
+ | 3.3548 | 0.9313 | 312 | 1.1975 |
366
+ | 3.1675 | 0.9343 | 313 | 1.1975 |
367
+ | 3.2788 | 0.9373 | 314 | 1.1972 |
368
+ | 3.1682 | 0.9403 | 315 | 1.1975 |
369
+ | 3.6201 | 0.9433 | 316 | 1.1973 |
370
+ | 2.9316 | 0.9463 | 317 | 1.1973 |
371
+ | 3.2871 | 0.9493 | 318 | 1.1970 |
372
+ | 3.0758 | 0.9522 | 319 | 1.1973 |
373
+ | 3.0506 | 0.9552 | 320 | 1.1972 |
374
+ | 3.0749 | 0.9582 | 321 | 1.1971 |
375
+ | 3.0325 | 0.9612 | 322 | 1.1969 |
376
+ | 3.0342 | 0.9642 | 323 | 1.1969 |
377
+ | 3.2879 | 0.9672 | 324 | 1.1969 |
378
+ | 2.9969 | 0.9701 | 325 | 1.1967 |
379
+ | 3.4164 | 0.9731 | 326 | 1.1967 |
380
+ | 3.3712 | 0.9761 | 327 | 1.1966 |
381
+ | 3.1877 | 0.9791 | 328 | 1.1967 |
382
+ | 3.3259 | 0.9821 | 329 | 1.1968 |
383
+ | 3.2571 | 0.9851 | 330 | 1.1965 |
384
+ | 3.0292 | 0.9881 | 331 | 1.1968 |
385
+ | 3.2312 | 0.9910 | 332 | 1.1966 |
386
+ | 3.3412 | 0.9940 | 333 | 1.1965 |
387
+ | 3.2653 | 0.9970 | 334 | 1.1966 |
388
+ | 3.3735 | 1.0 | 335 | 1.1965 |
389
+
390
+
391
+ ### Framework versions
392
+
393
+ - Transformers 4.48.0
394
+ - Pytorch 2.5.1+cu124
395
+ - Datasets 3.2.0
396
+ - Tokenizers 0.21.0
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+ {
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+ "_name_or_path": "Qwen/Qwen2.5-0.5B",
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+ "max_window_layers": 24,
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+ "model_type": "qwen2",
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+ "num_attention_heads": 14,
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+ "num_hidden_layers": 24,
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+ "num_key_value_heads": 2,
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+ "rms_norm_eps": 1e-06,
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+ "rope_scaling": null,
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+ "use_sliding_window": false,
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