| --- |
| library_name: transformers |
| base_model: allenai/scibert_scivocab_uncased |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: scibert-acm-multilabel |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # scibert-acm-multilabel |
|
|
| This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0238 |
| - F1 Average Per Sample: 0.4069 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 3e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 16 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 4 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 Average Per Sample | |
| |:-------------:|:-----:|:-----:|:---------------:|:---------------------:| |
| | 0.0565 | 1.0 | 5000 | 0.0291 | 0.2295 | |
| | 0.0513 | 2.0 | 10000 | 0.0251 | 0.3690 | |
| | 0.0459 | 3.0 | 15000 | 0.0240 | 0.3994 | |
| | 0.0443 | 4.0 | 20000 | 0.0238 | 0.4069 | |
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|
| ### Framework versions |
|
|
| - Transformers 5.0.0 |
| - Pytorch 2.11.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
|
|
