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---
license: gemma
library_name: peft
tags:
- generated_from_trainer
base_model: google/gemma-1.1-2b-it
metrics:
- accuracy
model-index:
- name: emotions_google_gemma
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. -->
# emotions_google_gemma
This model is a fine-tuned version of [google/gemma-1.1-2b-it](https://huggingface.co/google/gemma-1.1-2b-it) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4858
- F1 Micro: 0.6961
- F1 Macro: 0.6067
- Accuracy: 0.2369
## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 0.7307 | 0.2067 | 20 | 0.6081 | 0.6151 | 0.4711 | 0.1709 |
| 0.5276 | 0.4134 | 40 | 0.5106 | 0.6760 | 0.5729 | 0.1676 |
| 0.5081 | 0.6202 | 60 | 0.4978 | 0.6922 | 0.5857 | 0.2006 |
| 0.5091 | 0.8269 | 80 | 0.4853 | 0.6908 | 0.6038 | 0.2052 |
| 0.4823 | 1.0336 | 100 | 0.4858 | 0.6961 | 0.6067 | 0.2369 |
| 0.3346 | 1.2403 | 120 | 0.5500 | 0.6663 | 0.5728 | 0.1702 |
| 0.3245 | 1.4470 | 140 | 0.5440 | 0.6816 | 0.5819 | 0.2052 |
| 0.3375 | 1.6537 | 160 | 0.5541 | 0.6808 | 0.5853 | 0.1987 |
| 0.3407 | 1.8605 | 180 | 0.5275 | 0.6875 | 0.5872 | 0.1916 |
| 0.2745 | 2.0672 | 200 | 0.6019 | 0.6928 | 0.5784 | 0.2311 |
| 0.1312 | 2.2739 | 220 | 0.7540 | 0.6750 | 0.5614 | 0.2097 |
| 0.1363 | 2.4806 | 240 | 0.7292 | 0.6805 | 0.5712 | 0.2078 |
| 0.1302 | 2.6873 | 260 | 0.7316 | 0.6846 | 0.5795 | 0.2045 |
| 0.125 | 2.8941 | 280 | 0.7491 | 0.6819 | 0.5711 | 0.2104 |
| 0.0877 | 3.1008 | 300 | 0.8069 | 0.6805 | 0.5651 | 0.2330 |
| 0.0457 | 3.3075 | 320 | 0.8849 | 0.6867 | 0.5592 | 0.2356 |
| 0.0453 | 3.5142 | 340 | 0.8583 | 0.6774 | 0.5626 | 0.2246 |
| 0.0429 | 3.7209 | 360 | 0.8338 | 0.6812 | 0.5675 | 0.2227 |
| 0.0463 | 3.9276 | 380 | 0.8497 | 0.6823 | 0.5735 | 0.2272 |
| 0.0256 | 4.1344 | 400 | 0.9236 | 0.6759 | 0.5607 | 0.2278 |
| 0.0155 | 4.3411 | 420 | 0.9380 | 0.6871 | 0.5651 | 0.2421 |
| 0.0127 | 4.5478 | 440 | 0.9505 | 0.6852 | 0.5646 | 0.2414 |
| 0.0129 | 4.7545 | 460 | 0.9438 | 0.6837 | 0.5658 | 0.2382 |
| 0.0123 | 4.9612 | 480 | 0.9431 | 0.6843 | 0.5666 | 0.2401 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |