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---
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
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