---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
model-index:
- name: tiny-llama-lora-no-grad
  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-lora-no-grad

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: 0.7206
- Accuracy: 0.8164
- Precision: 0.8231
- Recall: 0.8164
- Precision Macro: 0.7396
- Recall Macro: 0.7117
- Macro Fpr: 0.0159
- Weighted Fpr: 0.0152
- Weighted Specificity: 0.9752
- Macro Specificity: 0.9865
- Weighted Sensitivity: 0.8226
- Macro Sensitivity: 0.7117
- F1 Micro: 0.8226
- F1 Macro: 0.7177
- F1 Weighted: 0.8190

## 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: 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: 15

### 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---------------:|:------------:|:---------:|:------------:|:--------------------:|:-----------------:|:--------------------:|:-----------------:|:--------:|:--------:|:-----------:|
| 1.1276        | 1.0   | 643  | 0.6705          | 0.8087   | 0.8055    | 0.8087 | 0.7053          | 0.6853       | 0.0172    | 0.0166       | 0.9742               | 0.9855            | 0.8087               | 0.6853            | 0.8087   | 0.6806   | 0.8034      |
| 0.503         | 2.0   | 1286 | 0.7206          | 0.8164   | 0.8231    | 0.8164 | 0.7746          | 0.7641       | 0.0163    | 0.0158       | 0.9773               | 0.9862            | 0.8164               | 0.7641            | 0.8164   | 0.7610   | 0.8154      |
| 0.3617        | 3.0   | 1929 | 0.8819          | 0.8164   | 0.8137    | 0.8164 | 0.7499          | 0.7170       | 0.0164    | 0.0158       | 0.9752               | 0.9861            | 0.8164               | 0.7170            | 0.8164   | 0.7242   | 0.8124      |
| 0.0618        | 4.0   | 2572 | 1.1434          | 0.8087   | 0.8107    | 0.8087 | 0.7673          | 0.7293       | 0.0173    | 0.0166       | 0.9727               | 0.9854            | 0.8087               | 0.7293            | 0.8087   | 0.7401   | 0.8074      |
| 0.0243        | 5.0   | 3215 | 1.2966          | 0.8110   | 0.8112    | 0.8110 | 0.7489          | 0.7164       | 0.0171    | 0.0164       | 0.9754               | 0.9858            | 0.8110               | 0.7164            | 0.8110   | 0.7228   | 0.8086      |
| 0.0121        | 6.0   | 3858 | 1.2965          | 0.8195   | 0.8175    | 0.8195 | 0.7312          | 0.7077       | 0.0162    | 0.0155       | 0.9752               | 0.9863            | 0.8195               | 0.7077            | 0.8195   | 0.7143   | 0.8170      |
| 0.0021        | 7.0   | 4501 | 1.3710          | 0.8187   | 0.8168    | 0.8187 | 0.7519          | 0.7112       | 0.0162    | 0.0156       | 0.9756               | 0.9863            | 0.8187               | 0.7112            | 0.8187   | 0.7165   | 0.8152      |
| 0.003         | 8.0   | 5144 | 1.3348          | 0.8203   | 0.8171    | 0.8203 | 0.7417          | 0.7073       | 0.0162    | 0.0154       | 0.9749               | 0.9863            | 0.8203               | 0.7073            | 0.8203   | 0.7159   | 0.8173      |
| 0.0023        | 9.0   | 5787 | 1.4038          | 0.8187   | 0.8149    | 0.8187 | 0.7548          | 0.7030       | 0.0163    | 0.0156       | 0.9742               | 0.9862            | 0.8187               | 0.7030            | 0.8187   | 0.7121   | 0.8141      |
| 0.0033        | 10.0  | 6430 | 1.4021          | 0.8203   | 0.8151    | 0.8203 | 0.7330          | 0.7110       | 0.0162    | 0.0154       | 0.9746               | 0.9863            | 0.8203               | 0.7110            | 0.8203   | 0.7152   | 0.8163      |
| 0.0017        | 11.0  | 7073 | 1.4001          | 0.8211   | 0.8178    | 0.8211 | 0.7361          | 0.7110       | 0.0160    | 0.0153       | 0.9753               | 0.9864            | 0.8211               | 0.7110            | 0.8211   | 0.7155   | 0.8179      |
| 0.0023        | 12.0  | 7716 | 1.4100          | 0.8226   | 0.8189    | 0.8226 | 0.7386          | 0.7127       | 0.0158    | 0.0152       | 0.9754               | 0.9865            | 0.8226               | 0.7127            | 0.8226   | 0.7177   | 0.8195      |
| 0.0034        | 13.0  | 8359 | 1.4273          | 0.8234   | 0.8192    | 0.8234 | 0.7385          | 0.7115       | 0.0158    | 0.0151       | 0.9757               | 0.9866            | 0.8234               | 0.7115            | 0.8234   | 0.7171   | 0.8201      |
| 0.0016        | 14.0  | 9002 | 1.4322          | 0.8226   | 0.8183    | 0.8226 | 0.7382          | 0.7111       | 0.0159    | 0.0152       | 0.9754               | 0.9865            | 0.8226               | 0.7111            | 0.8226   | 0.7168   | 0.8192      |
| 0.0006        | 15.0  | 9645 | 1.4401          | 0.8226   | 0.8178    | 0.8226 | 0.7396          | 0.7117       | 0.0159    | 0.0152       | 0.9752               | 0.9865            | 0.8226               | 0.7117            | 0.8226   | 0.7177   | 0.8190      |


### Framework versions

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