peft generated_from_trainer base_model:decapoda-research/llama-7b-hf license:other region:us
---
license: other
base_model: decapoda-research/llama-7b-hf
tags:
- generated_from_trainer
model-index:
- name: llama-fintech-13
  results: []
library_name: peft
---

<!-- 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. -->

# llama-fintech-13

This model is a fine-tuned version of [decapoda-research/llama-7b-hf](https://huggingface.co/decapoda-research/llama-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1889

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: QuantizationMethod.BITS_AND_BYTES
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: float32
### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 1234
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.4519        | 0.15  | 50   | 2.4590          |
| 2.2828        | 0.3   | 100  | 2.1885          |
| 1.9233        | 0.45  | 150  | 1.5158          |
| 1.6426        | 0.6   | 200  | 1.2491          |
| 1.6084        | 0.76  | 250  | 1.1512          |
| 1.5972        | 0.91  | 300  | 1.1561          |
| 1.5723        | 1.06  | 350  | 1.1782          |
| 1.5798        | 1.21  | 400  | 1.1833          |
| 1.566         | 1.36  | 450  | 1.1831          |
| 1.5625        | 1.51  | 500  | 1.1870          |
| 1.5514        | 1.66  | 550  | 1.1839          |
| 1.5381        | 1.81  | 600  | 1.1758          |
| 1.5518        | 1.96  | 650  | 1.1780          |
| 1.5321        | 2.12  | 700  | 1.1735          |
| 1.5406        | 2.27  | 750  | 1.1768          |
| 1.5275        | 2.42  | 800  | 1.1784          |
| 1.543         | 2.57  | 850  | 1.1788          |
| 1.5292        | 2.72  | 900  | 1.1851          |
| 1.5471        | 2.87  | 950  | 1.1820          |
| 1.509         | 3.02  | 1000 | 1.1858          |
| 1.5281        | 3.17  | 1050 | 1.1778          |
| 1.5146        | 3.33  | 1100 | 1.1835          |
| 1.5086        | 3.48  | 1150 | 1.1843          |
| 1.5379        | 3.63  | 1200 | 1.1854          |
| 1.5295        | 3.78  | 1250 | 1.1835          |
| 1.5185        | 3.93  | 1300 | 1.1871          |
| 1.5261        | 4.08  | 1350 | 1.1863          |
| 1.5215        | 4.23  | 1400 | 1.1873          |
| 1.5209        | 4.38  | 1450 | 1.1900          |
| 1.518         | 4.53  | 1500 | 1.1891          |
| 1.5287        | 4.69  | 1550 | 1.1887          |
| 1.5141        | 4.84  | 1600 | 1.1875          |
| 1.5263        | 4.99  | 1650 | 1.1889          |


### Framework versions

- PEFT 0.6.0.dev0
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3
