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Finetuned raygx/GPT2-Nepali-Casual-LM model for generating Covid-News; 10 Epochs
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---
tags:
- generated_from_keras_callback
model-index:
- name: Covid-News-Headline-Generator
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. -->
# Covid-News-Headline-Generator
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 5.6414
- Validation Loss: 6.3015
- Epoch: 9
## 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': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.001}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 6.2059 | 6.6394 | 0 |
| 6.1308 | 6.6034 | 1 |
| 6.0590 | 6.5447 | 2 |
| 5.9910 | 6.5061 | 3 |
| 5.9264 | 6.4637 | 4 |
| 5.8640 | 6.4168 | 5 |
| 5.8058 | 6.3805 | 6 |
| 5.7492 | 6.3604 | 7 |
| 5.6948 | 6.3189 | 8 |
| 5.6414 | 6.3015 | 9 |
### Framework versions
- Transformers 4.28.1
- TensorFlow 2.11.0
- Datasets 2.1.0
- Tokenizers 0.13.3