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---
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 |