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---
license: apache-2.0
base_model: google/flan-t5-large
tags:
- generated_from_keras_callback
model-index:
- name: t5-large-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-large-mmlu-qa2a
This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1713
- Validation Loss: 0.2345
- Epoch: 1
<pre>{'eval_loss': 2.5656020641326904,
'eval_bleu': 8.103035378131528,
'eval_rouge1': 19.62,
'eval_rouge2': 6.75,
'eval_rougeL': 18.24,
'eval_rougeLsum': 18.24,
'eval_exact': 0.002608162012887389,
'eval_runtime': 704.3448,
'eval_samples_per_second': 18.508,
'eval_steps_per_second': 0.579}</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 |
|:----------:|:---------------:|:-----:|
| 0.3748 | 0.2314 | 0 |
| 0.1713 | 0.2345 | 1 |
### Framework versions
- Transformers 4.31.0
- TensorFlow 2.12.0
- Tokenizers 0.13.3
|