README.md

metadata

license: llama2
library_name: peft
tags:
  - generated_from_trainer
base_model: codellama/CodeLlama-7b-Instruct-hf
metrics:
  - accuracy
  - bleu
  - sacrebleu
  - rouge
model-index:
  - name: >-
      CodeLlama-7b-Instruct-hf_Fi__CMP_TR_size_304_epochs_10_2024-06-22_21-11-23_3558625
    results: []

CodeLlama-7b-Instruct-hf_Fi__CMP_TR_size_304_epochs_10_2024-06-22_21-11-23_3558625

This model is a fine-tuned version of codellama/CodeLlama-7b-Instruct-hf on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.9442
• Accuracy: 0.464
• Chrf: 0.282
• Bleu: 0.212
• Sacrebleu: 0.2
• Rouge1: 0.473
• Rouge2: 0.304
• Rougel: 0.447
• Rougelsum: 0.467
• Meteor: 0.474

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
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 304
• training_steps: 3040

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Chrf	Bleu	Sacrebleu	Rouge1	Rouge2	Rougel	Rougelsum	Meteor
0.7293	1.0	304	2.8400	0.471	0.109	0.089	0.1	0.318	0.168	0.304	0.297	0.274
0.043	2.0	608	3.2408	0.498	0.051	0.019	0.0	0.162	0.063	0.136	0.142	0.216
0.0514	3.0	912	2.8322	0.478	0.156	0.059	0.1	0.3	0.145	0.284	0.289	0.289
0.0145	4.0	1216	2.5898	0.478	0.101	0.064	0.1	0.263	0.167	0.258	0.258	0.32
0.8203	5.0	1520	2.7395	0.478	0.16	0.049	0.0	0.306	0.114	0.284	0.298	0.27
0.0546	6.0	1824	2.8379	0.458	0.052	0.022	0.0	0.068	0.0	0.056	0.057	0.21
0.0352	7.0	2128	2.6987	0.481	0.165	0.133	0.1	0.356	0.246	0.352	0.355	0.33
0.042	8.0	2432	2.0781	0.481	0.264	0.169	0.2	0.421	0.261	0.403	0.421	0.431
0.0124	9.0	2736	1.9029	0.464	0.293	0.222	0.2	0.466	0.304	0.445	0.465	0.473
0.0382	10.0	3040	1.9442	0.464	0.282	0.212	0.2	0.473	0.304	0.447	0.467	0.474

Framework versions

• PEFT 0.7.1
• Transformers 4.37.0
• Pytorch 2.2.1+cu121
• Datasets 2.20.0
• Tokenizers 0.15.2