| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: google/t5-small-lm-adapt |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: test1 |
| | 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. --> |
| |
|
| | # test1 |
| |
|
| | This model is a fine-tuned version of [google/t5-small-lm-adapt](https://huggingface.co/google/t5-small-lm-adapt) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.5772 |
| | - Exact Match Acc: 0.0118 |
| |
|
| | ## 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: 0.005 |
| | - train_batch_size: 128 |
| | - eval_batch_size: 128 |
| | - seed: 42 |
| | - 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: cosine |
| | - lr_scheduler_warmup_steps: 0.1 |
| | - num_epochs: 3.0 |
| | - label_smoothing_factor: 0.1 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Exact Match Acc | |
| | |:-------------:|:------:|:----:|:---------------:|:---------------:| |
| | | 1.6493 | 0.4348 | 50 | 1.6531 | 0.0011 | |
| | | 1.6842 | 0.8696 | 100 | 1.6311 | 0.0022 | |
| | | 1.6140 | 1.3043 | 150 | 1.6110 | 0.0054 | |
| | | 1.6240 | 1.7391 | 200 | 1.5943 | 0.0097 | |
| | | 1.5772 | 2.1739 | 250 | 1.5823 | 0.0108 | |
| | | 1.5760 | 2.6087 | 300 | 1.5772 | 0.0118 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 5.2.0 |
| | - Pytorch 2.10.0+cu128 |
| | - Datasets 4.5.0 |
| | - Tokenizers 0.22.2 |
| |
|
