|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- itihasa |
|
metrics: |
|
- bleu |
|
model-index: |
|
- name: M2M101 |
|
results: |
|
- task: |
|
name: Sequence-to-sequence Language Modeling |
|
type: text2text-generation |
|
dataset: |
|
name: itihasa |
|
type: itihasa |
|
config: Itihasa |
|
split: test |
|
args: Itihasa |
|
metrics: |
|
- name: Bleu |
|
type: bleu |
|
value: 0.0 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# M2M101 |
|
|
|
This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the itihasa dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 7.7213 |
|
- Bleu: 0.0 |
|
- Gen Len: 2.0 |
|
- Meteor: 0.0 |
|
|
|
## 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: 5 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | Meteor | |
|
|:-------------:|:-----:|:-----:|:---------------:|:----:|:-------:|:------:| |
|
| 0.0001 | 1.0 | 4698 | 7.5812 | 0.0 | 2.0 | 0.0 | |
|
| 0.0 | 2.0 | 9396 | 7.0783 | 0.0 | 2.0 | 0.0 | |
|
| 0.0 | 3.0 | 14094 | 8.0417 | 0.0 | 2.0 | 0.0 | |
|
| 0.0 | 4.0 | 18792 | 7.7102 | 0.0 | 2.0 | 0.0 | |
|
| 0.0 | 5.0 | 23490 | 7.7213 | 0.0 | 2.0 | 0.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.28.0 |
|
- Pytorch 2.3.1+cu118 |
|
- Datasets 2.12.0 |
|
- Tokenizers 0.13.3 |
|
|
