|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: google/mt5-small |
|
tags: |
|
- generated_from_keras_callback |
|
model-index: |
|
- name: pakawadeep/mt5-small-finetuned-ctfl-backtranslation_7k |
|
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. --> |
|
|
|
# pakawadeep/mt5-small-finetuned-ctfl-backtranslation_7k |
|
|
|
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Train Loss: 4.4260 |
|
- Validation Loss: 4.1643 |
|
- Train Bleu: 0.0 |
|
- Train Gen Len: 127.0 |
|
- Epoch: 29 |
|
|
|
## 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': 0.01} |
|
- training_precision: float32 |
|
|
|
### Training results |
|
|
|
| Train Loss | Validation Loss | Train Bleu | Train Gen Len | Epoch | |
|
|:----------:|:---------------:|:----------:|:-------------:|:-----:| |
|
| 18.4580 | 9.0813 | 0.0013 | 3.0 | 0 | |
|
| 10.6168 | 8.0760 | 0.0008 | 50.0 | 1 | |
|
| 8.9972 | 7.4303 | 0.0003 | 127.0 | 2 | |
|
| 8.2615 | 7.1119 | 0.0010 | 3.0 | 3 | |
|
| 7.8727 | 6.9450 | 0.0 | 2.0 | 4 | |
|
| 7.6314 | 6.8080 | 0.0 | 2.0 | 5 | |
|
| 7.4404 | 6.6029 | 0.0 | 2.0 | 6 | |
|
| 7.2126 | 6.2358 | 0.0003 | 127.0 | 7 | |
|
| 6.9077 | 5.6784 | 0.0003 | 127.0 | 8 | |
|
| 6.5300 | 5.3165 | 0.0003 | 127.0 | 9 | |
|
| 6.2332 | 5.0961 | 0.0003 | 127.0 | 10 | |
|
| 5.9571 | 4.9619 | 0.0003 | 127.0 | 11 | |
|
| 5.7344 | 4.8588 | 0.0 | 7.0 | 12 | |
|
| 5.5347 | 4.7700 | 0.0 | 127.0 | 13 | |
|
| 5.4059 | 4.7055 | 0.0005 | 127.0 | 14 | |
|
| 5.2839 | 4.6485 | 0.0004 | 127.0 | 15 | |
|
| 5.1769 | 4.5958 | 0.0 | 127.0 | 16 | |
|
| 5.0864 | 4.5455 | 0.0 | 127.0 | 17 | |
|
| 5.0025 | 4.5005 | 0.0 | 127.0 | 18 | |
|
| 4.9161 | 4.4589 | 0.6412 | 127.0 | 19 | |
|
| 4.8523 | 4.4206 | 0.8846 | 127.0 | 20 | |
|
| 4.7860 | 4.3832 | 0.0 | 10.0 | 21 | |
|
| 4.7340 | 4.3479 | 0.0 | 10.0 | 22 | |
|
| 4.6707 | 4.3200 | 0.0 | 10.0 | 23 | |
|
| 4.6181 | 4.2951 | 0.0 | 10.0 | 24 | |
|
| 4.5780 | 4.2621 | 0.0 | 14.0 | 25 | |
|
| 4.5309 | 4.2380 | 0.0 | 127.0 | 26 | |
|
| 4.4944 | 4.2097 | 5.1292 | 29.0 | 27 | |
|
| 4.4613 | 4.1865 | 0.0 | 127.0 | 28 | |
|
| 4.4260 | 4.1643 | 0.0 | 127.0 | 29 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- TensorFlow 2.17.0 |
|
- Datasets 3.0.0 |
|
- Tokenizers 0.19.1 |
|
|
