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---
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: morbius
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. -->
# morbius
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3311
- Bleu: 0.0490
- Precisions: [0.12658339197748064, 0.058000714881448825, 0.031020853918560506, 0.0276665140764477]
- Brevity Penalty: 0.9781
- Length Ratio: 0.9783
- Translation Length: 45472
- Reference Length: 46479
## 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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:--------------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|
| 2.6085 | 1.0 | 2630 | 2.3793 | 0.0398 | [0.11484440108136675, 0.05086452177719413, 0.022402389588222743, 0.019262093750807972] | 1.0 | 1.0585 | 49197 | 46479 |
| 2.5537 | 2.0 | 5260 | 2.3538 | 0.0451 | [0.12435074854873206, 0.053338059789672695, 0.02736549165120594, 0.024163621427155037] | 0.9858 | 0.9859 | 45822 | 46479 |
| 2.427 | 3.0 | 7890 | 2.3412 | 0.0478 | [0.12566410537870473, 0.05610922151130985, 0.029971974257836827, 0.026891236083357122] | 0.9798 | 0.9800 | 45550 | 46479 |
| 2.3716 | 4.0 | 10520 | 2.3347 | 0.0487 | [0.12663965838169275, 0.0574505431946487, 0.030477866031926728, 0.027230821761893922] | 0.9823 | 0.9825 | 45665 | 46479 |
| 2.3494 | 5.0 | 13150 | 2.3311 | 0.0490 | [0.12658339197748064, 0.058000714881448825, 0.031020853918560506, 0.0276665140764477] | 0.9781 | 0.9783 | 45472 | 46479 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
|