---
library_name: peft
tags:
- generated_from_trainer
base_model: TheBloke/Llama-2-7B-fp16
model-index:
- name: Saiga_timelist_task30steps
  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. -->

# Saiga_timelist_task30steps

This model is a fine-tuned version of [TheBloke/Llama-2-7B-fp16](https://huggingface.co/TheBloke/Llama-2-7B-fp16) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7980

## 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: 5e-06
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5376        | 0.05  | 2    | 1.7979          |
| 1.6041        | 0.1   | 4    | 1.7978          |
| 1.6858        | 0.15  | 6    | 1.7979          |
| 1.7722        | 0.21  | 8    | 1.7979          |
| 1.6524        | 0.26  | 10   | 1.7979          |
| 1.6374        | 0.31  | 12   | 1.7979          |
| 1.7269        | 0.36  | 14   | 1.7979          |
| 1.7028        | 0.41  | 16   | 1.7978          |
| 1.6422        | 0.46  | 18   | 1.7980          |
| 1.666         | 0.52  | 20   | 1.7979          |
| 1.5679        | 0.57  | 22   | 1.7977          |
| 1.7614        | 0.62  | 24   | 1.7978          |
| 1.7053        | 0.67  | 26   | 1.7978          |
| 1.7438        | 0.72  | 28   | 1.7981          |
| 1.8348        | 0.77  | 30   | 1.7980          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2