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---
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: l3.1-8b-inst-fft-induction-barc-heavy-200k-old-200k-lr1e-5-ep2
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. -->
# l3.1-8b-inst-fft-induction-barc-heavy-200k-old-200k-lr1e-5-ep2
This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2709
## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 128
- total_eval_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2817 | 1.0 | 2995 | 0.2818 |
| 0.2432 | 2.0 | 5990 | 0.2709 |
### Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu124
- Datasets 3.0.2
- Tokenizers 0.19.1
|