Hugging Face's logo

GlycerinLOL
/
LLM_Teached_Bart_From_Scratch

Text2Text Generation
Transformers
TensorBoard
Safetensors
bart
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
GlycerinLOL commited on
Commit
a7630b1
•
1 Parent(s): 685b7de

Model save

Browse files
Files changed (3) hide show
  1. README.md +33 -25
  2. model.safetensors +1 -1
  3. runs/Mar04_16-15-55_oi5vv8ctr1709312124223-tkfr5/events.out.tfevents.1709540166.oi5vv8ctr1709312124223-tkfr5.35385.0 +2 -2
README.md CHANGED
@@ -20,12 +20,12 @@ should probably proofread and complete it, then remove this comment. -->
20
 
21
  This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
22
  It achieves the following results on the evaluation set:
23
- - Loss: 1.5434
24
- - Rouge1: 0.4476
25
- - Rouge2: 0.2292
26
- - Rougel: 0.3868
27
- - Rougelsum: 0.3865
28
- - Gen Len: 19.9007
29
  - Precision: 0.9159
30
  - Recall: 0.8916
31
  - F1: 0.9034
@@ -55,29 +55,37 @@ The following hyperparameters were used during training:
55
  - total_train_batch_size: 96
56
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
57
  - lr_scheduler_type: linear
58
- - num_epochs: 16
59
  - mixed_precision_training: Native AMP
60
 
61
  ### Training results
62
 
63
- | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Precision | Recall | F1 |
64
- |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:---------:|:------:|:------:|
65
- | 1.836 | 1.0 | 521 | 1.5560 | 0.4155 | 0.2028 | 0.3561 | 0.3559 | 19.9745 | 0.9105 | 0.8843 | 0.8971 |
66
- | 1.5951 | 2.0 | 1042 | 1.5004 | 0.4333 | 0.2136 | 0.3695 | 0.3694 | 19.9353 | 0.9115 | 0.8886 | 0.8997 |
67
- | 1.469 | 3.0 | 1563 | 1.4691 | 0.4355 | 0.2176 | 0.3729 | 0.3728 | 19.9385 | 0.912 | 0.8888 | 0.9001 |
68
- | 1.373 | 4.0 | 2084 | 1.4658 | 0.4311 | 0.2164 | 0.3706 | 0.3704 | 19.9647 | 0.9137 | 0.8877 | 0.9003 |
69
- | 1.2902 | 5.0 | 2605 | 1.4542 | 0.4368 | 0.2218 | 0.3762 | 0.376 | 19.9498 | 0.9136 | 0.8887 | 0.9008 |
70
- | 1.222 | 6.0 | 3126 | 1.4584 | 0.4407 | 0.223 | 0.3802 | 0.3798 | 19.9425 | 0.914 | 0.8902 | 0.9018 |
71
- | 1.1655 | 7.0 | 3647 | 1.4709 | 0.4404 | 0.2246 | 0.3806 | 0.3803 | 19.9327 | 0.9145 | 0.89 | 0.9019 |
72
- | 1.11 | 8.0 | 4168 | 1.4724 | 0.4435 | 0.2269 | 0.383 | 0.3828 | 19.9084 | 0.9153 | 0.8906 | 0.9026 |
73
- | 1.0629 | 9.0 | 4689 | 1.4853 | 0.4431 | 0.2273 | 0.3832 | 0.383 | 19.928 | 0.9155 | 0.8908 | 0.9028 |
74
- | 1.023 | 10.0 | 5210 | 1.5033 | 0.4409 | 0.2247 | 0.3819 | 0.3818 | 19.944 | 0.9152 | 0.8897 | 0.9021 |
75
- | 0.9862 | 11.0 | 5731 | 1.5074 | 0.4479 | 0.2278 | 0.3862 | 0.386 | 19.9124 | 0.9158 | 0.8916 | 0.9034 |
76
- | 0.957 | 12.0 | 6252 | 1.5184 | 0.4461 | 0.2264 | 0.3846 | 0.3847 | 19.9033 | 0.9159 | 0.8909 | 0.903 |
77
- | 0.9315 | 13.0 | 6773 | 1.5269 | 0.4473 | 0.2284 | 0.386 | 0.3858 | 19.9084 | 0.9156 | 0.8912 | 0.9031 |
78
- | 0.9093 | 14.0 | 7294 | 1.5311 | 0.4453 | 0.2273 | 0.3846 | 0.3843 | 19.9135 | 0.9155 | 0.8909 | 0.9029 |
79
- | 0.8927 | 15.0 | 7815 | 1.5351 | 0.4457 | 0.2267 | 0.3842 | 0.384 | 19.9065 | 0.9156 | 0.8909 | 0.9029 |
80
- | 0.8773 | 16.0 | 8336 | 1.5434 | 0.4476 | 0.2292 | 0.3868 | 0.3865 | 19.9007 | 0.9159 | 0.8916 | 0.9034 |
 
 
 
 
 
 
 
 
81
 
82
 
83
  ### Framework versions
 
20
 
21
  This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
22
  It achieves the following results on the evaluation set:
23
+ - Loss: 1.6053
24
+ - Rouge1: 0.4481
25
+ - Rouge2: 0.2283
26
+ - Rougel: 0.3861
27
+ - Rougelsum: 0.3863
28
+ - Gen Len: 19.9029
29
  - Precision: 0.9159
30
  - Recall: 0.8916
31
  - F1: 0.9034
 
55
  - total_train_batch_size: 96
56
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
57
  - lr_scheduler_type: linear
58
+ - num_epochs: 24
59
  - mixed_precision_training: Native AMP
60
 
61
  ### Training results
62
 
63
+ | Training Loss | Epoch | Step | F1 | Gen Len | Validation Loss | Precision | Recall | Rouge1 | Rouge2 | Rougel | Rougelsum |
64
+ |:-------------:|:-----:|:-----:|:------:|:-------:|:---------------:|:---------:|:------:|:------:|:------:|:------:|:---------:|
65
+ | 1.836 | 1.0 | 521 | 0.8971 | 19.9745 | 1.5560 | 0.9105 | 0.8843 | 0.4155 | 0.2028 | 0.3561 | 0.3559 |
66
+ | 1.5951 | 2.0 | 1042 | 0.8997 | 19.9353 | 1.5004 | 0.9115 | 0.8886 | 0.4333 | 0.2136 | 0.3695 | 0.3694 |
67
+ | 1.469 | 3.0 | 1563 | 0.9001 | 19.9385 | 1.4691 | 0.912 | 0.8888 | 0.4355 | 0.2176 | 0.3729 | 0.3728 |
68
+ | 1.373 | 4.0 | 2084 | 0.9003 | 19.9647 | 1.4658 | 0.9137 | 0.8877 | 0.4311 | 0.2164 | 0.3706 | 0.3704 |
69
+ | 1.2902 | 5.0 | 2605 | 0.9008 | 19.9498 | 1.4542 | 0.9136 | 0.8887 | 0.4368 | 0.2218 | 0.3762 | 0.376 |
70
+ | 1.222 | 6.0 | 3126 | 0.9018 | 19.9425 | 1.4584 | 0.914 | 0.8902 | 0.4407 | 0.223 | 0.3802 | 0.3798 |
71
+ | 1.1655 | 7.0 | 3647 | 0.9019 | 19.9327 | 1.4709 | 0.9145 | 0.89 | 0.4404 | 0.2246 | 0.3806 | 0.3803 |
72
+ | 1.11 | 8.0 | 4168 | 0.9026 | 19.9084 | 1.4724 | 0.9153 | 0.8906 | 0.4435 | 0.2269 | 0.383 | 0.3828 |
73
+ | 1.0629 | 9.0 | 4689 | 0.9028 | 19.928 | 1.4853 | 0.9155 | 0.8908 | 0.4431 | 0.2273 | 0.3832 | 0.383 |
74
+ | 1.023 | 10.0 | 5210 | 0.9021 | 19.944 | 1.5033 | 0.9152 | 0.8897 | 0.4409 | 0.2247 | 0.3819 | 0.3818 |
75
+ | 0.9862 | 11.0 | 5731 | 0.9034 | 19.9124 | 1.5074 | 0.9158 | 0.8916 | 0.4479 | 0.2278 | 0.3862 | 0.386 |
76
+ | 0.957 | 12.0 | 6252 | 0.903 | 19.9033 | 1.5184 | 0.9159 | 0.8909 | 0.4461 | 0.2264 | 0.3846 | 0.3847 |
77
+ | 0.9315 | 13.0 | 6773 | 0.9031 | 19.9084 | 1.5269 | 0.9156 | 0.8912 | 0.4473 | 0.2284 | 0.386 | 0.3858 |
78
+ | 0.9093 | 14.0 | 7294 | 0.9029 | 19.9135 | 1.5311 | 0.9155 | 0.8909 | 0.4453 | 0.2273 | 0.3846 | 0.3843 |
79
+ | 0.8927 | 15.0 | 7815 | 0.9029 | 19.9065 | 1.5351 | 0.9156 | 0.8909 | 0.4457 | 0.2267 | 0.3842 | 0.384 |
80
+ | 0.8773 | 16.0 | 8336 | 0.9025 | 19.9425 | 1.5440 | 0.9151 | 0.8905 | 0.4427 | 0.225 | 0.382 | 0.382 |
81
+ | 0.8806 | 17.0 | 8857 | 0.9036 | 19.8851 | 1.5510 | 0.9159 | 0.8919 | 0.4495 | 0.2279 | 0.3868 | 0.3869 |
82
+ | 0.8683 | 18.0 | 9378 | 1.5679 | 0.4473 | 0.2282 | 0.3856 | 0.3857 | 19.8829| 0.9161 | 0.8921 | 0.9038 |
83
+ | 0.8413 | 19.0 | 9899 | 1.5745 | 0.4492 | 0.2282 | 0.3861 | 0.3864 | 19.9135| 0.9159 | 0.8918 | 0.9035 |
84
+ | 0.8257 | 20.0 | 10420 | 1.5835 | 0.4471 | 0.2266 | 0.3852 | 0.3853 | 19.8996| 0.9153 | 0.8915 | 0.9031 |
85
+ | 0.8097 | 21.0 | 10941 | 1.5957 | 0.4472 | 0.2271 | 0.3856 | 0.3856 | 19.9073| 0.9156 | 0.8919 | 0.9034 |
86
+ | 0.7926 | 22.0 | 11462 | 1.5956 | 0.4479 | 0.2282 | 0.3855 | 0.3857 | 19.892 | 0.9159 | 0.8916 | 0.9034 |
87
+ | 0.7841 | 23.0 | 11983 | 1.5990 | 0.4444 | 0.2261 | 0.3833 | 0.3834 | 19.912 | 0.9155 | 0.8908 | 0.9028 |
88
+ | 0.7669 | 24.0 | 12504 | 1.6053 | 0.4481 | 0.2283 | 0.3861 | 0.3863 | 19.9029| 0.9159 | 0.8916 | 0.9034 |
89
 
90
 
91
  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:44ce9fed33fe35b1a82babaea272ecb8d1e2c5f9c708b425b5f81a337343d310
3
  size 1625426996
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a0a3083777d6824a935113052da781583d125a5ddb5140744efaac3f4aca3ef3
3
  size 1625426996
runs/Mar04_16-15-55_oi5vv8ctr1709312124223-tkfr5/events.out.tfevents.1709540166.oi5vv8ctr1709312124223-tkfr5.35385.0 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:e0be1e28cb97df2f19531ddc3274689d23c875260e0e62bcef70e8c113781333
3
- size 10708
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f542fe20f6c9d2c02b20645ea99370490c3e6ea5f522a2ad3498493bbe65bc30
3
+ size 11736