---
base_model: RefalMachine/llama3_extended_darulm_20_05_24_part1-2_64000_bpe_mean_init_03_07_24
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: llama3_extended_darulm_20_05_24_part1-2_64000_bpe_part1_lr2e4_bs256
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# llama3_extended_darulm_20_05_24_part1-2_64000_bpe_part1_lr2e4_bs256

This model is a fine-tuned version of [RefalMachine/llama3_extended_darulm_20_05_24_part1-2_64000_bpe_mean_init_03_07_24](https://huggingface.co/RefalMachine/llama3_extended_darulm_20_05_24_part1-2_64000_bpe_mean_init_03_07_24) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1597
- Accuracy: 0.5489

## 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
- distributed_type: multi-GPU
- num_devices: 32
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.4497        | 0.09  | 2000  | 2.2890          | 0.5302   |
| 2.4021        | 0.18  | 4000  | 2.2496          | 0.5356   |
| 2.3883        | 0.28  | 6000  | 2.2251          | 0.5390   |
| 2.3684        | 0.37  | 8000  | 2.2056          | 0.5416   |
| 2.3547        | 0.46  | 10000 | 2.1889          | 0.5438   |
| 2.3271        | 0.55  | 12000 | 2.1759          | 0.5459   |
| 2.3153        | 0.64  | 14000 | 2.1664          | 0.5476   |
| 2.3175        | 0.73  | 16000 | 2.1618          | 0.5485   |
| 2.3013        | 0.83  | 18000 | 2.1599          | 0.5488   |
| 2.3075        | 0.92  | 20000 | 2.1597          | 0.5489   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.3.0a0+6ddf5cf85e.nv24.04
- Datasets 2.18.0
- Tokenizers 0.15.2