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---
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: Helsinki-NLPopus-mt-tc-big-en-moroccain_dialect
results: []
pipeline_tag: translation
---
<!-- 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. -->
<!-- in this model i use transfer learning for translate english to Moroccain dialect (darija). -->
<!-- about dataset used for training model : I used about 18,000 pairs of English and Moroccain Dialect. -->
<!-- my model is trained three times, the last being one epoch. -->
# Helsinki-NLPopus-mt-tc-big-en-moroccain_dialect
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6930
- Bleu: 50.0607
- Gen Len: 14.7048
## Model description
MarianConfig {
"_name_or_path": "/content/drive/MyDrive/Colab Notebooks/big_helsinki_eng_dar",
"activation_dropout": 0.0,
"activation_function": "relu",
"architectures": [
"MarianMTModel"
],
"attention_dropout": 0.0,
"bad_words_ids": [
[
61246
]
],
"bos_token_id": 0,
"classifier_dropout": 0.0,
"d_model": 1024,
"decoder_attention_heads": 16,
"decoder_ffn_dim": 4096,
"decoder_layerdrop": 0.0,
"decoder_layers": 6,
"decoder_start_token_id": 61246,
"decoder_vocab_size": 61247,
"dropout": 0.1,
"encoder_attention_heads": 16,
"encoder_ffn_dim": 4096,
"encoder_layerdrop": 0.0,
"encoder_layers": 6,
"eos_token_id": 25897,
"forced_eos_token_id": 25897,
"init_std": 0.02,
"is_encoder_decoder": true,
"max_length": 512,
"max_position_embeddings": 1024,
"model_type": "marian",
"normalize_embedding": false,
"num_beams": 4,
"num_hidden_layers": 6,
"pad_token_id": 61246,
"scale_embedding": true,
"share_encoder_decoder_embeddings": true,
"static_position_embeddings": true,
"torch_dtype": "float32",
"transformers_version": "4.28.0",
"use_cache": true,
"vocab_size": 61247
}
## Intended uses & limitations
More information needed
## Training and evaluation data
DatasetDict({
train: Dataset({
features: ['input_ids', 'attention_mask', 'labels'],
num_rows: 15443
})
test: Dataset({
features: ['input_ids', 'attention_mask', 'labels'],
num_rows: 813
})
})
## Training procedure
Using transfer learning due to limited data in the Moroccan dialect.
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 4000
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.617 | 1.0 | 1931 | 0.6930 | 50.0607 | 14.7048 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3 |