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---
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: meta-llama/Llama-2-13b-hf
metrics:
- accuracy
- precision
- recall
model-index:
- name: Llama2_13B_Task2_semantic_pred
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. -->
# Llama2_13B_Task2_semantic_pred
This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3818
- Accuracy: 0.9087
- Precision: 0.9087
- Recall: 0.9087
- F1 score: 0.9087
## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Accuracy | F1 score | Precision | Recall | Validation Loss |
|:-------------:|:------:|:----:|:--------:|:--------:|:---------:|:------:|:---------------:|
| 0.4564 | 0.2604 | 200 | 0.8214 | 0.8198 | 0.8311 | 0.8214 | 0.4378 |
| 0.3824 | 0.5208 | 400 | 0.8279 | 0.8279 | 0.8279 | 0.8279 | 0.4660 |
| 0.3609 | 0.7812 | 600 | 0.8631 | 0.8630 | 0.8635 | 0.8631 | 0.3303 |
| 0.3065 | 1.0417 | 800 | 0.8696 | 0.8695 | 0.8724 | 0.8696 | 0.3470 |
| 0.1987 | 1.3021 | 1000 | 0.8722 | 0.8722 | 0.8733 | 0.8722 | 0.3563 |
| 0.2043 | 1.5625 | 1200 | 0.9022 | 0.9020 | 0.9051 | 0.9022 | 0.3349 |
| 0.2193 | 1.8229 | 1400 | 0.8996 | 0.8996 | 0.8997 | 0.8996 | 0.3166 |
| 0.1674 | 2.0833 | 1600 | 0.8931 | 0.8930 | 0.8937 | 0.8931 | 0.3300 |
| 0.1226 | 2.3438 | 1800 | 0.3672 | 0.9087 | 0.9094 | 0.9087 | 0.9087 |
| 0.123 | 2.6042 | 2000 | 0.3862 | 0.9074 | 0.9091 | 0.9074 | 0.9073 |
| 0.0792 | 2.8646 | 2200 | 0.3818 | 0.9087 | 0.9087 | 0.9087 | 0.9087 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |