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fine_tuned_XLM-roberta

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mehdie/fine_tuned_xlm-roberta

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  1. README.md +58 -38
  2. model.safetensors +1 -1
  3. runs/Apr16_10-26-16_nv-ai-03.srv.aau.dk/events.out.tfevents.1713255977.nv-ai-03.srv.aau.dk.3594521.0 +3 -0
  4. runs/Apr16_10-26-16_nv-ai-03.srv.aau.dk/events.out.tfevents.1713256288.nv-ai-03.srv.aau.dk.3594521.1 +3 -0
  5. runs/Apr22_08-18-38_a256-a40-07.srv.aau.dk/events.out.tfevents.1713766722.a256-a40-07.srv.aau.dk.340138.0 +3 -0
  6. runs/Apr22_08-18-38_a256-a40-07.srv.aau.dk/events.out.tfevents.1713767043.a256-a40-07.srv.aau.dk.340138.1 +3 -0
  7. tokenizer.json +2 -2
  8. training_args.bin +1 -1
README.md CHANGED
@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3472
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- - F1: 0.4364
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- - F5: 0.4521
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- - Precision: 0.4
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- - Recall: 0.48
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  ## Model description
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@@ -43,49 +43,69 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 128
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- - eval_batch_size: 128
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  - seed: 42
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  - distributed_type: multi-GPU
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 30
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 | F5 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:|
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- | No log | 1.0 | 17 | 0.2280 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 2.0 | 34 | 0.2387 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 3.0 | 51 | 0.2550 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 4.0 | 68 | 0.2357 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 5.0 | 85 | 0.2311 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 6.0 | 102 | 0.2319 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 7.0 | 119 | 0.2380 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 8.0 | 136 | 0.2160 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 9.0 | 153 | 0.2329 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 10.0 | 170 | 0.2216 | 0.0 | 0.0 | 0.0 | 0.0 |
69
- | No log | 11.0 | 187 | 0.2187 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 12.0 | 204 | 0.2311 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 13.0 | 221 | 0.2216 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 14.0 | 238 | 0.2320 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 15.0 | 255 | 0.2472 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 16.0 | 272 | 0.2486 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 17.0 | 289 | 0.2607 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 18.0 | 306 | 0.2394 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 19.0 | 323 | 0.2566 | 0.1053 | 0.0835 | 0.3333 | 0.0625 |
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- | No log | 20.0 | 340 | 0.3055 | 0.3019 | 0.3557 | 0.2162 | 0.5 |
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- | No log | 21.0 | 357 | 0.2681 | 0.3902 | 0.4260 | 0.32 | 0.5 |
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- | No log | 22.0 | 374 | 0.2436 | 0.3529 | 0.3611 | 0.3333 | 0.375 |
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- | No log | 23.0 | 391 | 0.2390 | 0.2667 | 0.2600 | 0.2857 | 0.25 |
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- | No log | 24.0 | 408 | 0.2663 | 0.4444 | 0.4641 | 0.4 | 0.5 |
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- | No log | 25.0 | 425 | 0.2556 | 0.5143 | 0.5317 | 0.4737 | 0.5625 |
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- | No log | 26.0 | 442 | 0.2492 | 0.4571 | 0.4726 | 0.4211 | 0.5 |
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- | No log | 27.0 | 459 | 0.2555 | 0.5 | 0.5222 | 0.45 | 0.5625 |
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- | No log | 28.0 | 476 | 0.2607 | 0.4865 | 0.5130 | 0.4286 | 0.5625 |
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- | No log | 29.0 | 493 | 0.2393 | 0.4706 | 0.4814 | 0.4444 | 0.5 |
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- | 0.2307 | 30.0 | 510 | 0.2577 | 0.5 | 0.5222 | 0.45 | 0.5625 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
89
 
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  ### Framework versions
 
19
 
20
  This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
21
  It achieves the following results on the evaluation set:
22
+ - Loss: 0.3144
23
+ - F1: 0.44
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+ - F5: 0.5013
25
+ - Precision: 0.3333
26
+ - Recall: 0.6471
27
 
28
  ## Model description
29
 
 
43
 
44
  The following hyperparameters were used during training:
45
  - learning_rate: 5e-05
46
+ - train_batch_size: 256
47
+ - eval_batch_size: 256
48
  - seed: 42
49
  - distributed_type: multi-GPU
50
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
51
  - lr_scheduler_type: linear
52
+ - num_epochs: 50
53
  - mixed_precision_training: Native AMP
54
 
55
  ### Training results
56
 
57
  | Training Loss | Epoch | Step | Validation Loss | F1 | F5 | Precision | Recall |
58
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:|
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+ | No log | 1.0 | 9 | 0.3437 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 2.0 | 18 | 0.3128 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 3.0 | 27 | 0.3089 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 4.0 | 36 | 0.3058 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 5.0 | 45 | 0.2960 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 6.0 | 54 | 0.2744 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 7.0 | 63 | 0.2674 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 8.0 | 72 | 0.2744 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 9.0 | 81 | 0.2745 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 10.0 | 90 | 0.2849 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 11.0 | 99 | 0.3079 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 12.0 | 108 | 0.2686 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 13.0 | 117 | 0.2856 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 14.0 | 126 | 0.3047 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 15.0 | 135 | 0.2697 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 16.0 | 144 | 0.2783 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 17.0 | 153 | 0.2816 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 18.0 | 162 | 0.2660 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 19.0 | 171 | 0.3168 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 20.0 | 180 | 0.2796 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 21.0 | 189 | 0.2956 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 22.0 | 198 | 0.2610 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 23.0 | 207 | 0.2680 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 24.0 | 216 | 0.2836 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 25.0 | 225 | 0.2841 | 0.0588 | 0.0499 | 0.1111 | 0.04 |
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+ | No log | 26.0 | 234 | 0.3023 | 0.2128 | 0.2077 | 0.2273 | 0.2 |
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+ | No log | 27.0 | 243 | 0.3097 | 0.2903 | 0.3135 | 0.2432 | 0.36 |
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+ | No log | 28.0 | 252 | 0.3118 | 0.2963 | 0.3049 | 0.2759 | 0.32 |
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+ | No log | 29.0 | 261 | 0.3110 | 0.3256 | 0.3065 | 0.3889 | 0.28 |
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+ | No log | 30.0 | 270 | 0.3261 | 0.2927 | 0.2700 | 0.375 | 0.24 |
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+ | No log | 31.0 | 279 | 0.3167 | 0.4 | 0.4144 | 0.3667 | 0.44 |
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+ | No log | 32.0 | 288 | 0.2997 | 0.2857 | 0.2663 | 0.3529 | 0.24 |
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+ | No log | 33.0 | 297 | 0.3202 | 0.3385 | 0.3712 | 0.275 | 0.44 |
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+ | No log | 34.0 | 306 | 0.2841 | 0.3922 | 0.3951 | 0.3846 | 0.4 |
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+ | No log | 35.0 | 315 | 0.3986 | 0.4048 | 0.4788 | 0.2881 | 0.68 |
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+ | No log | 36.0 | 324 | 0.2881 | 0.4082 | 0.4050 | 0.4167 | 0.4 |
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+ | No log | 37.0 | 333 | 0.2719 | 0.3500 | 0.3195 | 0.4667 | 0.28 |
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+ | No log | 38.0 | 342 | 0.3239 | 0.4615 | 0.5062 | 0.375 | 0.6 |
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+ | No log | 39.0 | 351 | 0.2652 | 0.4906 | 0.5014 | 0.4643 | 0.52 |
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+ | No log | 40.0 | 360 | 0.2813 | 0.5 | 0.5213 | 0.4516 | 0.56 |
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+ | No log | 41.0 | 369 | 0.3664 | 0.4507 | 0.5081 | 0.3478 | 0.64 |
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+ | No log | 42.0 | 378 | 0.2577 | 0.4651 | 0.4379 | 0.5556 | 0.4 |
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+ | No log | 43.0 | 387 | 0.3193 | 0.4928 | 0.5507 | 0.3864 | 0.68 |
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+ | No log | 44.0 | 396 | 0.2627 | 0.4615 | 0.4684 | 0.4444 | 0.48 |
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+ | No log | 45.0 | 405 | 0.2850 | 0.4643 | 0.4841 | 0.4194 | 0.52 |
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+ | No log | 46.0 | 414 | 0.2971 | 0.5574 | 0.5986 | 0.4722 | 0.68 |
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+ | No log | 47.0 | 423 | 0.2804 | 0.5185 | 0.5336 | 0.4828 | 0.56 |
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+ | No log | 48.0 | 432 | 0.2845 | 0.5091 | 0.5274 | 0.4667 | 0.56 |
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+ | No log | 49.0 | 441 | 0.3005 | 0.5312 | 0.5797 | 0.4359 | 0.68 |
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+ | No log | 50.0 | 450 | 0.2981 | 0.5079 | 0.5514 | 0.4211 | 0.64 |
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  ### Framework versions
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