---
license: other
base_model: google/gemma-2b
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: gemma_2b_patent
  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. -->

# gemma_2b_patent

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8299
- Accuracy: 0.7138
- F1 Macro: 0.6753
- F1 Micro: 0.7138

## 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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 1.4602        | 0.13  | 50   | 1.3969          | 0.5022   | 0.3597   | 0.5022   |
| 1.0803        | 0.26  | 100  | 1.0653          | 0.6256   | 0.5392   | 0.6256   |
| 1.0025        | 0.38  | 150  | 0.9539          | 0.6728   | 0.6122   | 0.6728   |
| 0.9107        | 0.51  | 200  | 0.9216          | 0.6872   | 0.6279   | 0.6872   |
| 0.9144        | 0.64  | 250  | 0.8769          | 0.697    | 0.6581   | 0.697    |
| 0.8844        | 0.77  | 300  | 0.8914          | 0.6924   | 0.6435   | 0.6924   |
| 0.8721        | 0.9   | 350  | 0.8546          | 0.705    | 0.6553   | 0.705    |
| 0.6636        | 1.02  | 400  | 0.8299          | 0.7138   | 0.6753   | 0.7138   |
| 0.5654        | 1.15  | 450  | 0.8772          | 0.7056   | 0.6600   | 0.7056   |
| 0.6037        | 1.28  | 500  | 0.8565          | 0.7082   | 0.6628   | 0.7082   |
| 0.5781        | 1.41  | 550  | 0.8828          | 0.7      | 0.6543   | 0.7      |
| 0.565         | 1.53  | 600  | 0.8785          | 0.703    | 0.6693   | 0.703    |
| 0.6175        | 1.66  | 650  | 0.8799          | 0.7064   | 0.6579   | 0.7064   |
| 0.565         | 1.79  | 700  | 0.8562          | 0.7114   | 0.6582   | 0.7114   |
| 0.5752        | 1.92  | 750  | 0.8662          | 0.7046   | 0.6641   | 0.7046   |
| 0.2302        | 2.05  | 800  | 0.9298          | 0.704    | 0.6587   | 0.704    |
| 0.2034        | 2.17  | 850  | 1.0142          | 0.7      | 0.6601   | 0.7      |
| 0.2071        | 2.3   | 900  | 1.0373          | 0.6912   | 0.6604   | 0.6912   |
| 0.1889        | 2.43  | 950  | 1.0462          | 0.6982   | 0.6593   | 0.6982   |
| 0.1642        | 2.56  | 1000 | 1.0561          | 0.6932   | 0.6577   | 0.6932   |
| 0.1446        | 2.69  | 1050 | 1.0697          | 0.6966   | 0.6621   | 0.6966   |
| 0.1334        | 2.81  | 1100 | 1.0655          | 0.698    | 0.6637   | 0.698    |
| 0.1266        | 2.94  | 1150 | 1.0705          | 0.696    | 0.6625   | 0.696    |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2