opt-125m-finetuned-mnli
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: 0.7805
- Accuracy: 0.5182
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 | 0.8038 | 0.5185 |
No log | 2.0 | 2 | 0.8023 | 0.5182 |
No log | 3.0 | 3 | 0.8011 | 0.5182 |
No log | 4.0 | 4 | 0.8003 | 0.5184 |
No log | 5.0 | 5 | 0.7993 | 0.5184 |
No log | 6.0 | 6 | 0.7982 | 0.5184 |
No log | 7.0 | 7 | 0.7974 | 0.5182 |
No log | 8.0 | 8 | 0.7968 | 0.5182 |
No log | 9.0 | 9 | 0.7962 | 0.5181 |
No log | 10.0 | 10 | 0.7960 | 0.5182 |
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