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t5-xl-tpu-jumoreski
Defetya/t5-xl-tpu-jumoreski
t5-xl-tpu-jumoreski is a machine learning model from Defetya. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Oct 2, 2023
- Updated
- Oct 2, 2023
- SHA
- d2d3625a
Base models
Model card
From the Hugging Face model README
<!-- 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-xl-tpu-jumoreski
This model is a fine-tuned version of ai-forever/FRED-T5-1.7B on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.3608
- Epoch: 7
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': 0.01, 'clipnorm': 1, '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': {'class_name': 'CosineDecay', 'config': {'initial_learning_rate': 2e-06, 'decay_steps': 8552, 'alpha': 5e-09, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: mixed_bfloat16
Training results
| Train Loss | Epoch |
|---|---|
| 0.3666 | 0 |
| 0.3650 | 1 |
| 0.3643 | 2 |
| 0.3627 | 3 |
| 0.3625 | 4 |
| 0.3613 | 5 |
| 0.3605 | 6 |
| 0.3608 | 7 |
Framework versions
- Transformers 4.33.3
- TensorFlow 2.12.0
- Datasets 2.14.5
- Tokenizers 0.13.3
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Oct 2, 2023
- Updated
- Oct 2, 2023