Add readme

README.md

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+---
+license: llama2
+base_model: codellama/CodeLlama-13b-Instruct-hf
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- bleu
+- sacrebleu
+- rouge
+model-index:
+- name: CodeLlama-13b-Instruct-hf_En__size_52_epochs_10_2024-06-21_06-37-42_3556410
+  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-13b-Instruct-hf_En__size_52_epochs_10_2024-06-21_06-37-42_3556410
+
+This model is a fine-tuned version of [codellama/CodeLlama-13b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-13b-Instruct-hf) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6986
+- Accuracy: 0.052
+- Chrf: 0.682
+- Bleu: 0.599
+- Sacrebleu: 0.6
+- Rouge1: 0.651
+- Rouge2: 0.434
+- Rougel: 0.601
+- Rougelsum: 0.644
+- Meteor: 0.54
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:-----:|:---------:|:------:|:------:|:------:|:---------:|:------:|
+| 0.5377        | 4.0   | 52   | 1.6208          | 0.06     | 0.637 | 0.525 | 0.5       | 0.619  | 0.387  | 0.564  | 0.608     | 0.488  |
+| 0.932         | 8.0   | 104  | 2.1202          | 0.05     | 0.554 | 0.452 | 0.5       | 0.569  | 0.313  | 0.515  | 0.566     | 0.485  |
+| 0.3679        | 12.0  | 156  | 1.9634          | 0.049    | 0.606 | 0.488 | 0.5       | 0.594  | 0.371  | 0.549  | 0.59      | 0.491  |
+| 0.3454        | 16.0  | 208  | 1.9613          | 0.053    | 0.601 | 0.487 | 0.5       | 0.571  | 0.325  | 0.524  | 0.566     | 0.504  |
+| 0.3294        | 20.0  | 260  | 1.8641          | 0.05     | 0.638 | 0.536 | 0.5       | 0.611  | 0.388  | 0.568  | 0.604     | 0.516  |
+| 0.5272        | 24.0  | 312  | 1.8354          | 0.052    | 0.644 | 0.535 | 0.5       | 0.609  | 0.368  | 0.559  | 0.603     | 0.531  |
+| 0.1871        | 28.0  | 364  | 1.7705          | 0.054    | 0.659 | 0.568 | 0.6       | 0.627  | 0.41   | 0.586  | 0.624     | 0.54   |
+| 0.4867        | 32.0  | 416  | 1.7689          | 0.052    | 0.665 | 0.571 | 0.6       | 0.63   | 0.406  | 0.579  | 0.624     | 0.562  |
+| 0.1634        | 36.0  | 468  | 1.6964          | 0.052    | 0.682 | 0.601 | 0.6       | 0.658  | 0.444  | 0.605  | 0.65      | 0.538  |
+| 0.3475        | 40.0  | 520  | 1.6986          | 0.052    | 0.682 | 0.599 | 0.6       | 0.651  | 0.434  | 0.601  | 0.644     | 0.54   |
+
+
+### Framework versions
+
+- Transformers 4.37.0
+- Pytorch 2.2.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.15.2