---
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: 0.4792
- F1 Micro: 0.6970
- F1 Macro: 0.6089
- Accuracy: 0.2104

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 0.7081        | 0.2067 | 20   | 0.6048          | 0.6244   | 0.5113   | 0.1528   |
| 0.5228        | 0.4134 | 40   | 0.5096          | 0.6713   | 0.5815   | 0.1883   |
| 0.5048        | 0.6202 | 60   | 0.4928          | 0.7002   | 0.5865   | 0.2155   |
| 0.5129        | 0.8269 | 80   | 0.4792          | 0.6970   | 0.6089   | 0.2104   |
| 0.4842        | 1.0336 | 100  | 0.4801          | 0.6972   | 0.6023   | 0.2369   |
| 0.3372        | 1.2403 | 120  | 0.5545          | 0.6687   | 0.5877   | 0.1761   |
| 0.3302        | 1.4470 | 140  | 0.5374          | 0.6895   | 0.6020   | 0.2019   |
| 0.3342        | 1.6537 | 160  | 0.5330          | 0.6860   | 0.5993   | 0.2117   |
| 0.3392        | 1.8605 | 180  | 0.5190          | 0.6894   | 0.5913   | 0.2006   |
| 0.2844        | 2.0672 | 200  | 0.5853          | 0.6891   | 0.5819   | 0.2369   |
| 0.1458        | 2.2739 | 220  | 0.7038          | 0.6743   | 0.5749   | 0.2097   |
| 0.1508        | 2.4806 | 240  | 0.6808          | 0.6802   | 0.5834   | 0.1994   |
| 0.1481        | 2.6873 | 260  | 0.7026          | 0.6773   | 0.5721   | 0.2      |
| 0.1378        | 2.8941 | 280  | 0.7336          | 0.6790   | 0.5768   | 0.2162   |
| 0.0961        | 3.1008 | 300  | 0.8397          | 0.6709   | 0.5465   | 0.2272   |
| 0.0552        | 3.3075 | 320  | 0.8260          | 0.6743   | 0.5654   | 0.2168   |
| 0.0509        | 3.5142 | 340  | 0.8692          | 0.6777   | 0.5666   | 0.2233   |
| 0.0489        | 3.7209 | 360  | 0.8505          | 0.6874   | 0.5722   | 0.2388   |
| 0.0526        | 3.9276 | 380  | 0.8269          | 0.6842   | 0.5778   | 0.2233   |
| 0.0278        | 4.1344 | 400  | 0.9280          | 0.6813   | 0.5557   | 0.2414   |
| 0.0187        | 4.3411 | 420  | 0.9390          | 0.6829   | 0.5588   | 0.2382   |
| 0.0169        | 4.5478 | 440  | 0.9510          | 0.6834   | 0.5612   | 0.2485   |
| 0.0158        | 4.7545 | 460  | 0.9325          | 0.6819   | 0.5612   | 0.2427   |
| 0.0161        | 4.9612 | 480  | 0.9311          | 0.6822   | 0.5634   | 0.2440   |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1