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