tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: Helsinki-NLPopus-mt-tc-big-en-moroccain_dialect
results: []
pipeline_tag: translation
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