| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: microsoft/deberta-v3-large |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: deberta-tweetqa-5ep |
| | 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. --> |
| |
|
| | # deberta-tweetqa-5ep |
| |
|
| | This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 3.7168 |
| |
|
| | ## 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: 2 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 8 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 10 |
| | - num_epochs: 5 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 2.7783 | 1.0 | 1 | 3.8975 | |
| | | 2.8494 | 2.0 | 2 | 3.8975 | |
| | | 2.8872 | 3.0 | 3 | 3.8877 | |
| | | 2.854 | 4.0 | 4 | 3.8198 | |
| | | 2.6379 | 5.0 | 5 | 3.7168 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.52.2 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.21.1 |
| |
|
