---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: flan_t5_small_amazon
  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. -->

# flan_t5_small_amazon

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6518
- Accuracy: 0.8096
- F1 Macro: 0.7882
- F1 Micro: 0.8096

## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 1.9282        | 0.13  | 50   | 1.5904          | 0.5738   | 0.4436   | 0.5738   |
| 1.1323        | 0.26  | 100  | 1.1076          | 0.6634   | 0.5641   | 0.6634   |
| 0.9976        | 0.39  | 150  | 0.9465          | 0.7207   | 0.6468   | 0.7207   |
| 0.928         | 0.53  | 200  | 0.8840          | 0.7332   | 0.6860   | 0.7332   |
| 0.974         | 0.66  | 250  | 0.8179          | 0.7523   | 0.7026   | 0.7523   |
| 0.8206        | 0.79  | 300  | 0.7982          | 0.7675   | 0.7182   | 0.7675   |
| 0.8863        | 0.92  | 350  | 0.7445          | 0.7773   | 0.7301   | 0.7773   |
| 0.713         | 1.05  | 400  | 0.7428          | 0.7740   | 0.7391   | 0.7740   |
| 0.6544        | 1.18  | 450  | 0.7234          | 0.7852   | 0.7379   | 0.7852   |
| 0.6034        | 1.32  | 500  | 0.7140          | 0.7925   | 0.7648   | 0.7925   |
| 0.588         | 1.45  | 550  | 0.7062          | 0.7931   | 0.7585   | 0.7931   |
| 0.6035        | 1.58  | 600  | 0.7112          | 0.7925   | 0.7480   | 0.7925   |
| 0.6616        | 1.71  | 650  | 0.6783          | 0.7938   | 0.7578   | 0.7938   |
| 0.6334        | 1.84  | 700  | 0.6816          | 0.8004   | 0.7851   | 0.8004   |
| 0.5872        | 1.97  | 750  | 0.6532          | 0.8037   | 0.7792   | 0.8037   |
| 0.4134        | 2.11  | 800  | 0.6601          | 0.8070   | 0.7858   | 0.8070   |
| 0.518         | 2.24  | 850  | 0.6772          | 0.8070   | 0.7858   | 0.8070   |
| 0.3891        | 2.37  | 900  | 0.6752          | 0.8090   | 0.7866   | 0.8090   |
| 0.3389        | 2.5   | 950  | 0.6639          | 0.8123   | 0.7914   | 0.8123   |
| 0.4166        | 2.63  | 1000 | 0.6590          | 0.8169   | 0.8010   | 0.8169   |
| 0.483         | 2.76  | 1050 | 0.6630          | 0.8149   | 0.7937   | 0.8149   |
| 0.4582        | 2.89  | 1100 | 0.6518          | 0.8096   | 0.7882   | 0.8096   |


### Framework versions

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