Add readme

README.md

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+---
+license: llama2
+base_model: codellama/CodeLlama-7b-Instruct-hf
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- bleu
+- sacrebleu
+- rouge
+model-index:
+- name: CodeLlama-7b-Instruct-hf_En__size_52_epochs_10_2024-06-21_06-58-10_3556411
+  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. -->
+
+# CodeLlama-7b-Instruct-hf_En__size_52_epochs_10_2024-06-21_06-58-10_3556411
+
+This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6041
+- Accuracy: 0.054
+- Chrf: 0.699
+- Bleu: 0.622
+- Sacrebleu: 0.6
+- Rouge1: 0.691
+- Rouge2: 0.483
+- Rougel: 0.637
+- Rougelsum: 0.682
+- Meteor: 0.56
+
+## 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: 0.001
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 3407
+- distributed_type: multi-GPU
+- num_devices: 4
+- total_train_batch_size: 4
+- total_eval_batch_size: 4
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 52
+- training_steps: 520
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Chrf  | Bleu  | Sacrebleu | Rouge1 | Rouge2 | Rougel | Rougelsum | Meteor |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:-----:|:---------:|:------:|:------:|:------:|:---------:|:------:|
+| 0.1805        | 4.0   | 52   | 1.4057          | 0.058    | 0.674 | 0.548 | 0.5       | 0.651  | 0.411  | 0.596  | 0.643     | 0.529  |
+| 0.9191        | 8.0   | 104  | 1.9644          | 0.05     | 0.619 | 0.49  | 0.5       | 0.593  | 0.36   | 0.55   | 0.588     | 0.503  |
+| 0.3517        | 12.0  | 156  | 1.8542          | 0.052    | 0.628 | 0.526 | 0.5       | 0.63   | 0.407  | 0.582  | 0.625     | 0.522  |
+| 0.4017        | 16.0  | 208  | 2.2165          | 0.057    | 0.565 | 0.428 | 0.4       | 0.529  | 0.276  | 0.474  | 0.523     | 0.462  |
+| 0.324         | 20.0  | 260  | 1.8054          | 0.055    | 0.648 | 0.551 | 0.6       | 0.631  | 0.415  | 0.586  | 0.623     | 0.527  |
+| 0.5071        | 24.0  | 312  | 1.7591          | 0.058    | 0.671 | 0.562 | 0.6       | 0.651  | 0.435  | 0.599  | 0.644     | 0.531  |
+| 0.1758        | 28.0  | 364  | 1.6743          | 0.054    | 0.683 | 0.585 | 0.6       | 0.671  | 0.464  | 0.62   | 0.663     | 0.553  |
+| 0.4696        | 32.0  | 416  | 1.6739          | 0.055    | 0.679 | 0.592 | 0.6       | 0.656  | 0.44   | 0.606  | 0.645     | 0.536  |
+| 0.1516        | 36.0  | 468  | 1.6355          | 0.054    | 0.689 | 0.611 | 0.6       | 0.679  | 0.473  | 0.627  | 0.669     | 0.554  |
+| 0.3236        | 40.0  | 520  | 1.6041          | 0.054    | 0.699 | 0.622 | 0.6       | 0.691  | 0.483  | 0.637  | 0.682     | 0.56   |
+
+
+### Framework versions
+
+- Transformers 4.37.0
+- Pytorch 2.2.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.15.2