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Siguiente-ia
/
PLEX-0.1-8b

Text Generation
Transformers
PyTorch
Safetensors
Spanish
llama
axolotl
Generated from Trainer
conversational
text-generation-inference
Inference Endpoints
Model card Files Community
PLEX-0.1-8b
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---
library_name: transformers
license: llama3.1
base_model: NousResearch/Meta-Llama-3.1-8B
tags:
- axolotl
- generated_from_trainer
datasets:
- Siguiente-ia/plex-v0.2
model-index:
- name: PLEX-0.1-8b
  results: []
language:
- es
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.6.0`
```yaml
base_model: NousResearch/Meta-Llama-3.1-8B
# Automatically upload checkpoint and final model to HF
hub_model_id: Siguiente-ia/PLEX-0.1-8b

load_in_8bit: false
load_in_4bit: false
strict: false
chat_template: chatml

datasets:
  - path: Siguiente-ia/plex-v0.2
    type: chat_template
    field_messages: messages
dataset_prepared_path: last_run_prepared
val_set_size: 0.05
output_dir: ./outputs/out

sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true

wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 1
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 2e-5

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 100
evals_per_epoch: 2
eval_table_size:
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  pad_token: <|end_of_text|>
```

</details><br>

# PLEX-0.1-8b

This model is a fine-tuned version of [NousResearch/Meta-Llama-3.1-8B](https://huggingface.co/NousResearch/Meta-Llama-3.1-8B) on the Siguiente-ia/plex-v0.2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6582

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8808        | 0.0019 | 1    | 0.8060          |
| 0.6044        | 0.5003 | 269  | 0.6582          |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.3.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0