llama3-fsdp-qlora / README.md
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---
license: llama3
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-70b
datasets:
- generator
model-index:
- name: llama3-fsdp-qlora
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. -->
# llama3-fsdp-qlora
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-70b](https://huggingface.co/meta-llama/Meta-Llama-3-70b) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6181
## 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: 8
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.6242 | 0.9892 | 46 | 1.6281 |
| 1.5831 | 2.0 | 93 | 1.6165 |
| 1.5587 | 2.9677 | 138 | 1.6181 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.1.0
- Datasets 2.18.0
- Tokenizers 0.19.1