---
base_model: barc0/cot-400k-barc-llama3.1-8b-ins-fft-transduction_lr1e-5_epoch3
library_name: peft
license: llama3.1
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: cot-trainset-ft-transduction-v2-lora-train
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# cot-trainset-ft-transduction-v2-lora-train

This model is a fine-tuned version of [barc0/cot-400k-barc-llama3.1-8b-ins-fft-transduction_lr1e-5_epoch3](https://huggingface.co./barc0/cot-400k-barc-llama3.1-8b-ins-fft-transduction_lr1e-5_epoch3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2107

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1316        | 1.0   | 155  | 0.1494          |
| 0.073         | 2.0   | 310  | 0.1669          |
| 0.0305        | 3.0   | 465  | 0.2107          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1