opt-125m-finetuned-mnli-mm
This model is a fine-tuned version of facebook/opt-125m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7598
- Accuracy: 0.4952
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 1 | 0.7366 | 0.4926 |
No log | 2.0 | 2 | 0.7388 | 0.5004 |
No log | 3.0 | 3 | 0.7405 | 0.5053 |
No log | 4.0 | 4 | 0.7420 | 0.5072 |
No log | 5.0 | 5 | 0.7433 | 0.5104 |
No log | 6.0 | 6 | 0.7445 | 0.5104 |
No log | 7.0 | 7 | 0.7456 | 0.5108 |
No log | 8.0 | 8 | 0.7464 | 0.5125 |
No log | 9.0 | 9 | 0.7469 | 0.5135 |
No log | 10.0 | 10 | 0.7470 | 0.5131 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Base model
facebook/opt-125m