File size: 2,604 Bytes
d095b61 | 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 | ---
base_model: NousResearch/Llama-2-7b-hf
library_name: peft
metrics:
- accuracy
- precision
- recall
- f1
tags:
- generated_from_trainer
model-index:
- name: Experiment-2
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. -->
# Experiment-2
This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6750
- Accuracy: 0.596
- Precision: 0.5869
- Recall: 0.6263
- F1: 0.6060
## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 0.9874 | 54 | 0.6970 | 0.532 | 0.5313 | 0.4785 | 0.5035 |
| No log | 1.9931 | 109 | 0.6923 | 0.508 | 0.5103 | 0.1989 | 0.2863 |
| 0.694 | 2.9989 | 164 | 0.6888 | 0.5413 | 0.5303 | 0.6586 | 0.5875 |
| 0.694 | 3.9863 | 218 | 0.6926 | 0.5187 | 0.6279 | 0.0726 | 0.1301 |
| 0.694 | 4.992 | 273 | 0.6778 | 0.5947 | 0.6269 | 0.4516 | 0.525 |
| 0.6841 | 5.9977 | 328 | 0.6738 | 0.5827 | 0.5582 | 0.7608 | 0.6439 |
| 0.6841 | 6.9851 | 382 | 0.6701 | 0.5893 | 0.6301 | 0.4167 | 0.5016 |
| 0.6841 | 7.9909 | 437 | 0.6717 | 0.6013 | 0.5835 | 0.6855 | 0.6304 |
| 0.6699 | 8.9966 | 492 | 0.6768 | 0.5787 | 0.5553 | 0.7554 | 0.6401 |
| 0.6699 | 9.8743 | 540 | 0.6750 | 0.596 | 0.5869 | 0.6263 | 0.6060 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.46.3
- Pytorch 2.3.1.post300
- Datasets 3.2.0
- Tokenizers 0.20.3 |