peft tensorboard safetensors trl sft generated_from_trainer base_model:NousResearch/Llama-2-7b-hf region:us
---
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: NousResearch/Llama-2-7b-hf
model-index:
- name: llama2-7b-dolly-15k-japanese-brainstorming
  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. -->

# llama2-7b-dolly-15k-japanese-brainstorming

This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0642
- Rouge Scores: {'rouge1': 0.9653633690526473, 'rouge2': 0.9344851380895685, 'rougeL': 0.9554449155418876, 'rougeLsum': 0.9653412268073773}
- Bleu Scores: [0.900726205206837, 0.8659579174904524, 0.8282110782853057, 0.788805544882148]
- Gen Len: 467.6554

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge Scores                                                                                                                | Bleu Scores                                                                      | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------:|:--------:|
| 0.9844        | 1.0   | 398  | 0.9678          | {'rouge1': 0.9691461778318393, 'rouge2': 0.9382969684393989, 'rougeL': 0.9578632643524403, 'rougeLsum': 0.9690528081779507} | [0.9044212000231915, 0.86963718873592, 0.8320476513312739, 0.7928883742871506]   | 467.6554 |
| 0.6979        | 2.0   | 796  | 0.9827          | {'rouge1': 0.9660674664057384, 'rouge2': 0.935760349759682, 'rougeL': 0.9563208459437473, 'rougeLsum': 0.9658214441757752}  | [0.9032042405966677, 0.8700278506363877, 0.8335211486398665, 0.7953375975436736] | 467.6554 |
| 0.4532        | 3.0   | 1194 | 1.0642          | {'rouge1': 0.9653633690526473, 'rouge2': 0.9344851380895685, 'rougeL': 0.9554449155418876, 'rougeLsum': 0.9653412268073773} | [0.900726205206837, 0.8659579174904524, 0.8282110782853057, 0.788805544882148]   | 467.6554 |


### Framework versions

- PEFT 0.8.2
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.2.dev0
- Tokenizers 0.15.2