---
base_model: barc0/cot-transduction-arc-heavy
datasets:
- barc0/cot_train_dataset_960_ms10_v2
- barc0/cot_rearc_dataset_100_ms10
- barc0/seeds_cot
library_name: peft
license: llama3.1
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: cot-trainset-ft-transduction-v3-lora-train
  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. -->

# cot-trainset-ft-transduction-v3-lora-train

This model is a fine-tuned version of [barc0/cot-transduction-arc-heavy](https://huggingface.co/barc0/cot-transduction-arc-heavy) on the barc0/cot_train_dataset_960_ms10_v2, the barc0/cot_rearc_dataset_100_ms10 and the barc0/seeds_cot datasets.
It achieves the following results on the evaluation set:
- Loss: 0.1921

## 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: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.1018        | 0.9982 | 277  | 0.1238          |
| 0.0822        | 1.9964 | 554  | 0.1333          |


### Framework versions

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