File size: 2,687 Bytes
204c879 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 | ---
library_name: transformers
license: other
# base_model: /inspire/hdd/ws-8207e9e2-e733-4eec-a475-cfa1c36480ba/embodied-multimodality/public/yli/workspace/Model/meta-llama/Llama-3.1-8B
base_model: meta-llama/Llama-3.1-8B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: llama
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. -->
# llama
This model is a fine-tuned version of [/inspire/hdd/ws-8207e9e2-e733-4eec-a475-cfa1c36480ba/embodied-multimodality/public/yli/workspace/Model/meta-llama/Llama-3.1-8B](https://huggingface.co//inspire/hdd/ws-8207e9e2-e733-4eec-a475-cfa1c36480ba/embodied-multimodality/public/yli/workspace/Model/meta-llama/Llama-3.1-8B) on the 2wikimultihopqa_train, the hotpotqa_train and the musique_train datasets.
It achieves the following results on the evaluation set:
- Loss: 0.1784
## 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: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.2074 | 0.1921 | 500 | 0.1999 |
| 0.2202 | 0.3843 | 1000 | 0.1942 |
| 0.1933 | 0.5764 | 1500 | 0.1811 |
| 0.1909 | 0.7686 | 2000 | 0.1720 |
| 0.1637 | 0.9607 | 2500 | 0.1639 |
| 0.0983 | 1.1528 | 3000 | 0.1664 |
| 0.1033 | 1.3450 | 3500 | 0.1602 |
| 0.1145 | 1.5371 | 4000 | 0.1557 |
| 0.105 | 1.7293 | 4500 | 0.1506 |
| 0.1008 | 1.9214 | 5000 | 0.1454 |
| 0.031 | 2.1136 | 5500 | 0.1753 |
| 0.0313 | 2.3057 | 6000 | 0.1777 |
| 0.0323 | 2.4978 | 6500 | 0.1765 |
| 0.0311 | 2.6900 | 7000 | 0.1781 |
| 0.0277 | 2.8821 | 7500 | 0.1787 |
### Framework versions
- Transformers 4.46.1
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3
|