roberta-vmw-mrqa-s
This model is a fine-tuned version of VMware/roberta-base-mrqa on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2333
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: 1e-05
- train_batch_size: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 500
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.149 | 0.0357 | 50 | 1.2558 |
| 1.1432 | 0.0715 | 100 | 1.2662 |
| 1.1559 | 0.1072 | 150 | 1.2555 |
| 1.2238 | 0.1430 | 200 | 1.2339 |
| 1.1742 | 0.1787 | 250 | 1.2422 |
| 1.169 | 0.2144 | 300 | 1.2393 |
| 1.1487 | 0.2502 | 350 | 1.2296 |
| 1.163 | 0.2859 | 400 | 1.2310 |
| 1.1779 | 0.3217 | 450 | 1.2311 |
| 1.1303 | 0.3574 | 500 | 1.2333 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
VMware/roberta-base-mrqa