End of training

README.md

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+---
+license: other
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: facebook/opt-1.3b
+metrics:
+- accuracy
+model-index:
+- name: opt-1.3b-finetuned-mnli
+  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. -->
+
+# opt-1.3b-finetuned-mnli
+
+This model is a fine-tuned version of [facebook/opt-1.3b](https://huggingface.co/facebook/opt-1.3b) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7762
+- Accuracy: 0.5027
+
+## 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    | 0.7791          | 0.5057   |
+| No log        | 2.0   | 2    | 0.7755          | 0.5033   |
+| No log        | 3.0   | 3    | 0.7731          | 0.5001   |
+| No log        | 4.0   | 4    | 0.7716          | 0.4973   |
+| No log        | 5.0   | 5    | 0.7705          | 0.4963   |
+| No log        | 6.0   | 6    | 0.7698          | 0.4972   |
+| No log        | 7.0   | 7    | 0.7694          | 0.4963   |
+| No log        | 8.0   | 8    | 0.7691          | 0.4966   |
+| No log        | 9.0   | 9    | 0.7690          | 0.4961   |
+| No log        | 10.0  | 10   | 0.7690          | 0.4972   |
+
+
+### 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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