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---
base_model: CohereForAI/aya-expanse-8b
library_name: peft
license: other
tags:
- llama-factory
- lora
- unsloth
- generated_from_trainer
model-index:
- name: la-cohere-aya-expanse-8b-8k_4bit_r32_alpha_16_lr1e-4_3ep
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. -->
# la-cohere-aya-expanse-8b-8k_4bit_r32_alpha_16_lr1e-4_3ep
This model is a fine-tuned version of [CohereForAI/aya-expanse-8b](https://huggingface.co./CohereForAI/aya-expanse-8b) on the la_chat_data_v4 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3464
## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Use 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: 2.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.5011 | 0.6649 | 10000 | 0.4348 |
| 0.4008 | 1.3299 | 20000 | 0.3684 |
| 0.4035 | 1.9948 | 30000 | 0.3464 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.46.1
- Pytorch 2.4.1+cu121
- Datasets 2.20.0
- Tokenizers 0.20.3 |