---
license: mit
tags:
- generated_from_trainer
datasets:
- iva_mt_wslot
metrics:
- bleu
model-index:
- name: iva_mt_wslot-m2m100_418M-en-pl-plaintext_10e
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: iva_mt_wslot
      type: iva_mt_wslot
      config: en-pl
      split: validation
      args: en-pl
    metrics:
    - name: Bleu
      type: bleu
      value: 41.3124
---

<!-- 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. -->

# iva_mt_wslot-m2m100_418M-en-pl-plaintext_10e

This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the iva_mt_wslot dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0169
- Bleu: 41.3124
- Gen Len: 15.5197

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.0169        | 1.0   | 5091  | 0.0162          | 36.663  | 15.6444 |
| 0.0124        | 2.0   | 10182 | 0.0151          | 38.36   | 15.6314 |
| 0.0086        | 3.0   | 15273 | 0.0150          | 39.3808 | 15.5507 |
| 0.0069        | 4.0   | 20364 | 0.0152          | 39.6307 | 15.5235 |
| 0.0049        | 5.0   | 25455 | 0.0156          | 40.4441 | 15.5911 |
| 0.0038        | 6.0   | 30546 | 0.0159          | 40.3781 | 15.47   |
| 0.0027        | 7.0   | 35637 | 0.0163          | 40.1339 | 15.4722 |
| 0.0021        | 8.0   | 40728 | 0.0166          | 41.4429 | 15.4906 |
| 0.0016        | 9.0   | 45819 | 0.0168          | 41.1024 | 15.5249 |
| 0.0012        | 10.0  | 50910 | 0.0169          | 41.3124 | 15.5197 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3