---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_keras_callback
model-index:
- name: t5-small-mmlu-qa2a
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# t5-small-mmlu-qa2a

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:
- Train Loss: 0.2046
- Validation Loss: 0.2880
- Epoch: 1

<pre>{'eval_loss': 3.1777148246765137,
 'eval_bleu': 8.258012778244474,
 'eval_rouge1': 19.05,
 'eval_rouge2': 6.45,
 'eval_rougeL': 17.73,
 'eval_rougeLsum': 17.73,
 'eval_exact': 0.0010739490641301012,
 'eval_runtime': 155.1163,
 'eval_samples_per_second': 84.04,
 'eval_steps_per_second': 2.63}</pre>

## 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:
- optimizer: {'name': 'Adafactor', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 0.001, 'beta_2_decay': -0.8, 'epsilon_1': 1e-30, 'epsilon_2': 0.001, 'clip_threshold': 1.0, 'relative_step': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 0.4413     | 0.2854          | 0     |
| 0.2046     | 0.2880          | 1     |


### Framework versions

- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.3
- Tokenizers 0.13.3