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---
library_name: transformers
license: apache-2.0
base_model: MubarakB/mt5_small_lg_en
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mt5_small_lg_inf_en
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_small_lg_inf_en
This model is a fine-tuned version of [MubarakB/mt5_small_lg_en](https://huggingface.co/MubarakB/mt5_small_lg_en) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4301
- Bleu: 0.3034
- Gen Len: 8.1551
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log | 1.0 | 138 | 0.4671 | 0.0646 | 9.4449 |
| No log | 2.0 | 276 | 0.4562 | 0.1318 | 7.8898 |
| No log | 3.0 | 414 | 0.4511 | 0.2119 | 7.9878 |
| 0.4729 | 4.0 | 552 | 0.4476 | 0.2133 | 8.1184 |
| 0.4729 | 5.0 | 690 | 0.4451 | 0.2128 | 8.0816 |
| 0.4729 | 6.0 | 828 | 0.4433 | 0.3272 | 7.9224 |
| 0.4729 | 7.0 | 966 | 0.4415 | 0.3383 | 7.6571 |
| 0.4479 | 8.0 | 1104 | 0.4401 | 0.3281 | 7.5347 |
| 0.4479 | 9.0 | 1242 | 0.4390 | 0.3296 | 7.4286 |
| 0.4479 | 10.0 | 1380 | 0.4378 | 0.3157 | 7.6 |
| 0.4418 | 11.0 | 1518 | 0.4367 | 0.3288 | 7.4327 |
| 0.4418 | 12.0 | 1656 | 0.4360 | 0.316 | 7.4857 |
| 0.4418 | 13.0 | 1794 | 0.4350 | 0.3167 | 7.4898 |
| 0.4418 | 14.0 | 1932 | 0.4342 | 0.3161 | 7.698 |
| 0.4347 | 15.0 | 2070 | 0.4337 | 0.316 | 7.849 |
| 0.4347 | 16.0 | 2208 | 0.4333 | 0.3177 | 7.6735 |
| 0.4347 | 17.0 | 2346 | 0.4326 | 0.3174 | 7.8082 |
| 0.4347 | 18.0 | 2484 | 0.4324 | 0.3167 | 7.8531 |
| 0.4315 | 19.0 | 2622 | 0.4319 | 0.3185 | 8.0163 |
| 0.4315 | 20.0 | 2760 | 0.4316 | 0.318 | 8.0449 |
| 0.4315 | 21.0 | 2898 | 0.4313 | 0.3171 | 8.0571 |
| 0.4289 | 22.0 | 3036 | 0.4311 | 0.3195 | 7.9837 |
| 0.4289 | 23.0 | 3174 | 0.4308 | 0.3188 | 8.049 |
| 0.4289 | 24.0 | 3312 | 0.4307 | 0.3048 | 8.0694 |
| 0.4289 | 25.0 | 3450 | 0.4304 | 0.3046 | 8.1306 |
| 0.4264 | 26.0 | 3588 | 0.4303 | 0.3041 | 8.1224 |
| 0.4264 | 27.0 | 3726 | 0.4302 | 0.3044 | 8.1592 |
| 0.4264 | 28.0 | 3864 | 0.4301 | 0.3046 | 8.1306 |
| 0.4256 | 29.0 | 4002 | 0.4301 | 0.3039 | 8.1429 |
| 0.4256 | 30.0 | 4140 | 0.4301 | 0.3034 | 8.1551 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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