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---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
model-index:
- name: mt5-base-ft-rf-02
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mt5-base-ft-rf-02
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4229
## 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:
- learning_rate: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 43.082 | 0.24 | 50 | 37.1069 |
| 34.6827 | 0.49 | 100 | 28.8296 |
| 21.0188 | 0.73 | 150 | 19.9344 |
| 18.3905 | 0.98 | 200 | 12.0120 |
| 14.342 | 1.22 | 250 | 9.2877 |
| 6.2116 | 1.46 | 300 | 6.1602 |
| 6.5474 | 1.71 | 350 | 4.6816 |
| 1.9222 | 1.95 | 400 | 2.6431 |
| 2.0579 | 2.2 | 450 | 1.2741 |
| 1.1028 | 2.44 | 500 | 0.9638 |
| 1.3341 | 2.68 | 550 | 0.8896 |
| 0.6531 | 2.93 | 600 | 0.8461 |
| 0.9805 | 3.17 | 650 | 0.7652 |
| 0.7167 | 3.41 | 700 | 0.7544 |
| 1.0224 | 3.66 | 750 | 0.7493 |
| 0.5367 | 3.9 | 800 | 0.7188 |
| 0.9352 | 4.15 | 850 | 0.6844 |
| 0.4927 | 4.39 | 900 | 0.6595 |
| 0.7141 | 4.63 | 950 | 0.6458 |
| 0.5773 | 4.88 | 1000 | 0.5911 |
| 0.4791 | 5.12 | 1050 | 0.5691 |
| 0.498 | 5.37 | 1100 | 0.5572 |
| 0.4306 | 5.61 | 1150 | 0.5315 |
| 0.334 | 5.85 | 1200 | 0.5123 |
| 0.3783 | 6.1 | 1250 | 0.4970 |
| 0.7719 | 6.34 | 1300 | 0.4774 |
| 0.3732 | 6.59 | 1350 | 0.4591 |
| 0.6203 | 6.83 | 1400 | 0.4482 |
| 0.4669 | 7.07 | 1450 | 0.4434 |
| 0.5568 | 7.32 | 1500 | 0.4307 |
| 0.6352 | 7.56 | 1550 | 0.4257 |
| 1.4137 | 7.8 | 1600 | 0.4229 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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