---
license: apache-2.0
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: tiny-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. -->

# tiny-llama

This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co./TinyLlama/TinyLlama-1.1B-Chat-v1.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2265
- Accuracy: 0.8327
- Precision: 0.8301
- Recall: 0.8327
- Precision Macro: 0.7955
- Recall Macro: 0.7536
- Macro Fpr: 0.0148
- Weighted Fpr: 0.0141
- Weighted Specificity: 0.9765
- Macro Specificity: 0.9873
- Weighted Sensitivity: 0.8327
- Macro Sensitivity: 0.7536
- F1 Micro: 0.8327
- F1 Macro: 0.7609
- F1 Weighted: 0.8291

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Precision Macro | Recall Macro | Macro Fpr | Weighted Fpr | Weighted Specificity | Macro Specificity | Weighted Sensitivity | Macro Sensitivity | F1 Micro | F1 Macro | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---------------:|:------------:|:---------:|:------------:|:--------------------:|:-----------------:|:--------------------:|:-----------------:|:--------:|:--------:|:-----------:|
| 1.0444        | 1.0   | 642  | 0.5968          | 0.8056   | 0.8050    | 0.8056 | 0.7122          | 0.6995       | 0.0175    | 0.0169       | 0.9730               | 0.9852            | 0.8056               | 0.6995            | 0.8056   | 0.6986   | 0.8014      |
| 0.4788        | 2.0   | 1284 | 0.6966          | 0.8195   | 0.8222    | 0.8195 | 0.8092          | 0.7825       | 0.0161    | 0.0155       | 0.9755               | 0.9863            | 0.8195               | 0.7825            | 0.8195   | 0.7849   | 0.8172      |
| 0.3354        | 3.0   | 1926 | 0.8046          | 0.8327   | 0.8276    | 0.8327 | 0.8058          | 0.7582       | 0.0148    | 0.0141       | 0.9758               | 0.9872            | 0.8327               | 0.7582            | 0.8327   | 0.7742   | 0.8282      |
| 0.0571        | 4.0   | 2569 | 1.1143          | 0.8265   | 0.8312    | 0.8265 | 0.7904          | 0.7763       | 0.0152    | 0.0148       | 0.9772               | 0.9869            | 0.8265               | 0.7763            | 0.8265   | 0.7690   | 0.8262      |
| 0.0187        | 5.0   | 3211 | 1.1104          | 0.8319   | 0.8316    | 0.8319 | 0.7745          | 0.7724       | 0.0149    | 0.0142       | 0.9770               | 0.9873            | 0.8319               | 0.7724            | 0.8319   | 0.7638   | 0.8303      |
| 0.0071        | 6.0   | 3853 | 1.1445          | 0.8242   | 0.8210    | 0.8242 | 0.7684          | 0.7384       | 0.0157    | 0.0150       | 0.9755               | 0.9866            | 0.8242               | 0.7384            | 0.8242   | 0.7451   | 0.8209      |
| 0.0002        | 7.0   | 4495 | 1.2032          | 0.8327   | 0.8302    | 0.8327 | 0.7985          | 0.7529       | 0.0148    | 0.0141       | 0.9765               | 0.9873            | 0.8327               | 0.7529            | 0.8327   | 0.7617   | 0.8293      |
| 0.0028        | 8.0   | 5138 | 1.1918          | 0.8257   | 0.8226    | 0.8257 | 0.7738          | 0.7493       | 0.0155    | 0.0149       | 0.9756               | 0.9868            | 0.8257               | 0.7493            | 0.8257   | 0.7552   | 0.8229      |
| 0.0           | 9.0   | 5780 | 1.2181          | 0.8311   | 0.8286    | 0.8311 | 0.7935          | 0.7522       | 0.0150    | 0.0143       | 0.9764               | 0.9872            | 0.8311               | 0.7522            | 0.8311   | 0.7592   | 0.8276      |
| 0.0018        | 10.0  | 6420 | 1.2265          | 0.8327   | 0.8301    | 0.8327 | 0.7955          | 0.7536       | 0.0148    | 0.0141       | 0.9765               | 0.9873            | 0.8327               | 0.7536            | 0.8327   | 0.7609   | 0.8291      |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.1