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---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: CIS6930_DAAGR_T5_emo
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. -->
# CIS6930_DAAGR_T5_emo
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.3698
- Train Accuracy: 0.9584
- Validation Loss: 0.4586
- Validation Accuracy: 0.9472
- Epoch: 14
## 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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 0.001, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.5130 | 0.9390 | 0.4789 | 0.9431 | 0 |
| 0.4570 | 0.9456 | 0.4682 | 0.9446 | 1 |
| 0.4434 | 0.9477 | 0.4624 | 0.9454 | 2 |
| 0.4334 | 0.9490 | 0.4594 | 0.9459 | 3 |
| 0.4250 | 0.9503 | 0.4570 | 0.9464 | 4 |
| 0.4180 | 0.9513 | 0.4556 | 0.9466 | 5 |
| 0.4114 | 0.9523 | 0.4545 | 0.9469 | 6 |
| 0.4052 | 0.9532 | 0.4537 | 0.9471 | 7 |
| 0.3997 | 0.9540 | 0.4541 | 0.9471 | 8 |
| 0.3943 | 0.9548 | 0.4533 | 0.9473 | 9 |
| 0.3891 | 0.9556 | 0.4538 | 0.9474 | 10 |
| 0.3838 | 0.9563 | 0.4549 | 0.9474 | 11 |
| 0.3791 | 0.9570 | 0.4558 | 0.9474 | 12 |
| 0.3744 | 0.9577 | 0.4573 | 0.9473 | 13 |
| 0.3698 | 0.9584 | 0.4586 | 0.9472 | 14 |
### Framework versions
- Transformers 4.27.4
- TensorFlow 2.11.0
- Datasets 2.11.0
- Tokenizers 0.13.2
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