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alex-apoha/esm_finetuned

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README.md CHANGED
@@ -14,7 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model was trained from scratch on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0238
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  ## Model description
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@@ -33,11 +33,11 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0004
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- - train_batch_size: 4
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  - eval_batch_size: 8
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  - seed: 42
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- - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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  - num_epochs: 50
@@ -46,20 +46,24 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.0478 | 1.0 | 32 | 0.0808 |
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- | 0.0265 | 2.0 | 64 | 0.0346 |
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- | 0.0412 | 3.0 | 96 | 0.0195 |
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- | 0.0201 | 4.0 | 128 | 0.0522 |
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- | 0.0286 | 5.0 | 160 | 0.0484 |
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- | 0.0175 | 6.0 | 192 | 0.0190 |
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- | 0.0163 | 7.0 | 224 | 0.0356 |
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- | 0.0094 | 8.0 | 256 | 0.0248 |
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- | 0.0047 | 9.0 | 288 | 0.0238 |
 
 
 
 
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  ### Framework versions
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- - Transformers 4.48.2
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- - Pytorch 2.6.0+cu124
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- - Datasets 3.2.0
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  - Tokenizers 0.21.0
 
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  This model was trained from scratch on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0143
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  ## Model description
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  ### Training hyperparameters
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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: 16
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  - eval_batch_size: 8
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  - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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  - num_epochs: 50
 
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 1.0 | 8 | 0.0703 |
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+ | 0.0992 | 2.0 | 16 | 0.0554 |
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+ | 0.0516 | 3.0 | 24 | 0.0550 |
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+ | 0.0533 | 4.0 | 32 | 0.0460 |
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+ | 0.0359 | 5.0 | 40 | 0.0361 |
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+ | 0.0359 | 6.0 | 48 | 0.0268 |
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+ | 0.027 | 7.0 | 56 | 0.0201 |
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+ | 0.0151 | 8.0 | 64 | 0.0151 |
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+ | 0.0138 | 9.0 | 72 | 0.0116 |
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+ | 0.0124 | 10.0 | 80 | 0.0094 |
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+ | 0.0124 | 11.0 | 88 | 0.0102 |
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+ | 0.0085 | 12.0 | 96 | 0.0106 |
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+ | 0.0062 | 13.0 | 104 | 0.0143 |
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  ### Framework versions
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+ - Transformers 4.48.1
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+ - Pytorch 2.4.1.post300
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+ - Datasets 2.2.1
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  - Tokenizers 0.21.0
best_model/config.json CHANGED
@@ -1,5 +1,5 @@
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  {
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- "_name_or_path": "./esm_mlm_cdr_pretrained_150M",
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  "architectures": [
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  "EsmForSequenceClassification"
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  ],
@@ -30,7 +30,7 @@
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  "problem_type": "regression",
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  "token_dropout": true,
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  "torch_dtype": "float32",
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- "transformers_version": "4.48.2",
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  "use_cache": true,
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  "vocab_list": null,
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  "vocab_size": 33
 
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  {
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+ "_name_or_path": "../data/esm_mlm_cdr_pretrained_150M",
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  "architectures": [
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  "EsmForSequenceClassification"
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  ],
 
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  "problem_type": "regression",
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  "token_dropout": true,
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  "torch_dtype": "float32",
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+ "transformers_version": "4.48.1",
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  "use_cache": true,
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  "vocab_list": null,
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  "vocab_size": 33
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