---
library_name: transformers
license: other
base_model: instruction-pretrain/finance-Llama3-8B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: pretrain_sft_finance
  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. -->

# pretrain_sft_finance

This model is a fine-tuned version of [instruction-pretrain/finance-Llama3-8B](https://huggingface.co/instruction-pretrain/finance-Llama3-8B) on the time_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2738

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 4.1092        | 0.0649 | 10   | 4.4912          |
| 2.1524        | 0.1299 | 20   | 1.8664          |
| 0.7796        | 0.1948 | 30   | 0.6781          |
| 0.3127        | 0.2597 | 40   | 0.2871          |
| 0.4223        | 0.3247 | 50   | 0.2762          |
| 0.2854        | 0.3896 | 60   | 0.2877          |
| 0.2908        | 0.4545 | 70   | 0.3328          |
| 0.4468        | 0.5195 | 80   | 0.3878          |
| 0.2962        | 0.5844 | 90   | 0.2747          |
| 0.2759        | 0.6494 | 100  | 0.2835          |
| 0.3065        | 0.7143 | 110  | 0.2901          |
| 0.2882        | 0.7792 | 120  | 0.2735          |
| 0.2945        | 0.8442 | 130  | 0.2920          |
| 0.2805        | 0.9091 | 140  | 0.2734          |
| 0.2696        | 0.9740 | 150  | 0.2738          |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1