---
license: mit
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: m2m100_lr_2e5_gradd_accum_1
  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. -->

# m2m100_lr_2e5_gradd_accum_1

This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2511
- Bleu: 10.7253
- Gen Len: 45.9543
- Meteor: 0.3079
- Chrf: 33.934

## 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: 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: 32.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len | Meteor | Chrf    |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:------:|:-------:|
| 3.6632        | 3.97  | 2406  | 2.8977          | 7.6826  | 49.2935 | 0.2567 | 28.2679 |
| 2.1329        | 7.94  | 4812  | 2.7600          | 10.0915 | 47.2241 | 0.2999 | 32.4294 |
| 1.552         | 11.91 | 7218  | 2.8218          | 10.3506 | 45.6178 | 0.3041 | 33.2923 |
| 1.1577        | 15.88 | 9624  | 2.9258          | 10.3313 | 46.668  | 0.3058 | 33.4639 |
| 0.8781        | 19.85 | 12030 | 3.0435          | 10.5266 | 46.2384 | 0.3063 | 33.6649 |
| 0.6935        | 23.82 | 14436 | 3.1381          | 10.4391 | 46.0441 | 0.3062 | 33.7686 |
| 0.5683        | 27.79 | 16842 | 3.2178          | 10.6801 | 45.8612 | 0.309  | 33.8163 |
| 0.5037        | 31.76 | 19248 | 3.2511          | 10.7253 | 45.9543 | 0.3079 | 33.934  |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.11.0+cu113
- Datasets 2.10.0
- Tokenizers 0.12.1