metadata
base_model: heisenberg1337/m2m100_418M_tq_fr_1
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: m2m100_418M_tq_fr_new_data
results: []
m2m100_418M_tq_fr_new_data
This model is a fine-tuned version of heisenberg1337/m2m100_418M_tq_fr_1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7732
- Bleu: 5.0521
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-06
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 0.7993 | 1.69 | 100 | 0.7767 | 4.9208 |
| 0.7761 | 3.38 | 200 | 0.7743 | 4.7089 |
| 0.7723 | 5.06 | 300 | 0.7726 | 4.8445 |
| 0.7585 | 6.75 | 400 | 0.7720 | 4.8352 |
| 0.7468 | 8.44 | 500 | 0.7732 | 5.1454 |
| 0.7331 | 10.13 | 600 | 0.7744 | 4.8311 |
| 0.7301 | 11.81 | 700 | 0.7732 | 5.0521 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3