ft-raft-hotpot / README.md
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finetuned-raft-hotpot-adapters
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---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
- generator
library_name: peft
license: llama3.1
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: ft-raft-hotpot
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. -->
# ft-raft-hotpot
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 generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8450
## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1399
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.61 | 0.0148 | 20 | 1.3531 |
| 1.1917 | 0.0295 | 40 | 1.0786 |
| 1.0438 | 0.0443 | 60 | 1.0227 |
| 1.0087 | 0.0590 | 80 | 0.9971 |
| 0.9835 | 0.0738 | 100 | 0.9795 |
| 0.9753 | 0.0885 | 120 | 0.9651 |
| 0.9586 | 0.1033 | 140 | 0.9521 |
| 0.9504 | 0.1180 | 160 | 0.9419 |
| 0.937 | 0.1328 | 180 | 0.9312 |
| 0.9242 | 0.1475 | 200 | 0.9203 |
| 0.9073 | 0.1623 | 220 | 0.9111 |
| 0.9017 | 0.1771 | 240 | 0.9023 |
| 0.8956 | 0.1918 | 260 | 0.8939 |
| 0.8824 | 0.2066 | 280 | 0.8856 |
| 0.8776 | 0.2213 | 300 | 0.8784 |
| 0.8755 | 0.2361 | 320 | 0.8710 |
| 0.8746 | 0.2508 | 340 | 0.8646 |
| 0.8569 | 0.2656 | 360 | 0.8592 |
| 0.8499 | 0.2803 | 380 | 0.8547 |
| 0.8514 | 0.2951 | 400 | 0.8509 |
| 0.8541 | 0.3098 | 420 | 0.8484 |
| 0.856 | 0.3246 | 440 | 0.8465 |
| 0.8397 | 0.3394 | 460 | 0.8455 |
| 0.8402 | 0.3541 | 480 | 0.8451 |
| 0.8497 | 0.3689 | 500 | 0.8450 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1