---
license: gemma
base_model: google/gemma-1.1-2b-it
tags:
- generated_from_trainer
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: 0.8963
- F1 Micro: 0.6927
- F1 Macro: 0.5713
- Accuracy: 0.2537

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 0.7843        | 0.1035 | 20   | 0.6332          | 0.6164   | 0.4369   | 0.1301   |
| 0.5717        | 0.2070 | 40   | 0.5575          | 0.6468   | 0.5359   | 0.1793   |
| 0.5341        | 0.3105 | 60   | 0.5292          | 0.6788   | 0.5562   | 0.2006   |
| 0.5054        | 0.4140 | 80   | 0.5143          | 0.6830   | 0.5716   | 0.2045   |
| 0.4748        | 0.5175 | 100  | 0.5039          | 0.6875   | 0.5797   | 0.1754   |
| 0.5144        | 0.6210 | 120  | 0.5028          | 0.6804   | 0.5988   | 0.1631   |
| 0.5055        | 0.7245 | 140  | 0.5101          | 0.6823   | 0.5728   | 0.2039   |
| 0.5124        | 0.8279 | 160  | 0.4851          | 0.6854   | 0.5947   | 0.1793   |
| 0.488         | 0.9314 | 180  | 0.4906          | 0.6777   | 0.5947   | 0.1638   |
| 0.4867        | 1.0349 | 200  | 0.4970          | 0.6845   | 0.6033   | 0.2227   |
| 0.3367        | 1.1384 | 220  | 0.5478          | 0.6977   | 0.5848   | 0.2188   |
| 0.3342        | 1.2419 | 240  | 0.5531          | 0.6860   | 0.5898   | 0.2110   |
| 0.3161        | 1.3454 | 260  | 0.5754          | 0.6719   | 0.5768   | 0.1955   |
| 0.3312        | 1.4489 | 280  | 0.5335          | 0.6840   | 0.5906   | 0.1961   |
| 0.3633        | 1.5524 | 300  | 0.5255          | 0.6799   | 0.5940   | 0.1883   |
| 0.3199        | 1.6559 | 320  | 0.5461          | 0.6722   | 0.5868   | 0.1922   |
| 0.3385        | 1.7594 | 340  | 0.5417          | 0.6888   | 0.5795   | 0.2149   |
| 0.3292        | 1.8629 | 360  | 0.5324          | 0.6883   | 0.5969   | 0.1981   |
| 0.3347        | 1.9664 | 380  | 0.5274          | 0.6890   | 0.5881   | 0.2006   |
| 0.2122        | 2.0699 | 400  | 0.6957          | 0.6755   | 0.5671   | 0.2350   |
| 0.1289        | 2.1734 | 420  | 0.6570          | 0.6814   | 0.5825   | 0.1974   |
| 0.1505        | 2.2768 | 440  | 0.6495          | 0.6854   | 0.5857   | 0.2117   |
| 0.1345        | 2.3803 | 460  | 0.7193          | 0.6813   | 0.5681   | 0.2045   |
| 0.1438        | 2.4838 | 480  | 0.7042          | 0.6782   | 0.5649   | 0.2065   |
| 0.14          | 2.5873 | 500  | 0.6777          | 0.6855   | 0.5826   | 0.2104   |
| 0.146         | 2.6908 | 520  | 0.6699          | 0.6837   | 0.5840   | 0.2129   |
| 0.138         | 2.7943 | 540  | 0.6954          | 0.6884   | 0.5820   | 0.2369   |
| 0.1302        | 2.8978 | 560  | 0.7090          | 0.6828   | 0.5777   | 0.2220   |
| 0.1324        | 3.0013 | 580  | 0.7075          | 0.6845   | 0.5818   | 0.2259   |
| 0.0472        | 3.1048 | 600  | 0.8346          | 0.6867   | 0.5575   | 0.2414   |
| 0.0544        | 3.2083 | 620  | 0.7725          | 0.6785   | 0.5706   | 0.2207   |
| 0.0483        | 3.3118 | 640  | 0.8136          | 0.6865   | 0.5659   | 0.2291   |
| 0.0465        | 3.4153 | 660  | 0.8333          | 0.6797   | 0.5613   | 0.2278   |
| 0.0511        | 3.5188 | 680  | 0.8234          | 0.6852   | 0.5641   | 0.2265   |
| 0.0511        | 3.6223 | 700  | 0.8298          | 0.6905   | 0.5712   | 0.2401   |
| 0.0406        | 3.7257 | 720  | 0.8292          | 0.6886   | 0.5721   | 0.2421   |
| 0.0565        | 3.8292 | 740  | 0.8266          | 0.6927   | 0.5721   | 0.2408   |
| 0.0554        | 3.9327 | 760  | 0.7764          | 0.6887   | 0.5765   | 0.2350   |
| 0.0319        | 4.0362 | 780  | 0.8450          | 0.6825   | 0.5650   | 0.2388   |
| 0.0161        | 4.1397 | 800  | 0.8948          | 0.6892   | 0.5648   | 0.2524   |
| 0.0174        | 4.2432 | 820  | 0.9146          | 0.6910   | 0.5659   | 0.2570   |
| 0.0168        | 4.3467 | 840  | 0.9068          | 0.6874   | 0.5657   | 0.2414   |
| 0.0184        | 4.4502 | 860  | 0.9225          | 0.6872   | 0.5615   | 0.2531   |
| 0.0123        | 4.5537 | 880  | 0.9062          | 0.6882   | 0.5639   | 0.2511   |
| 0.0149        | 4.6572 | 900  | 0.9087          | 0.6889   | 0.5660   | 0.2492   |
| 0.0199        | 4.7607 | 920  | 0.8948          | 0.6917   | 0.5722   | 0.2472   |
| 0.0144        | 4.8642 | 940  | 0.8944          | 0.6929   | 0.5724   | 0.2518   |
| 0.015         | 4.9677 | 960  | 0.8963          | 0.6925   | 0.5709   | 0.2531   |


### Framework versions

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