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Training complete

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.gitignore ADDED
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+ checkpoint-*/
README.md ADDED
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+ ---
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+ license: mit
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+ tags:
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+ - translation
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+ - generated_from_trainer
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+ datasets:
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+ - kde4
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+ model-index:
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+ - name: m2m100_418M-fr
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+ results:
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+ - task:
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+ name: Sequence-to-sequence Language Modeling
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+ type: text2text-generation
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+ dataset:
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+ name: kde4
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+ type: kde4
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+ args: en-fr
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+ ---
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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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+
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+ # m2m100_418M-fr
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+
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+ This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the kde4 dataset.
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 64
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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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+ - num_epochs: 3
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+
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+ ### Framework versions
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+
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+ - Transformers 4.11.0.dev0
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+ - Pytorch 1.9.0+cpu
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+ - Datasets 1.16.1
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+ - Tokenizers 0.10.3
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+ {
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+ "_name_or_path": "facebook/m2m100_418M",
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+ "activation_dropout": 0.0,
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+ "activation_function": "relu",
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+ "M2M100ForConditionalGeneration"
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+ "decoder_ffn_dim": 4096,
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+ "decoder_layerdrop": 0.05,
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+ "decoder_layers": 12,
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+ "decoder_start_token_id": 2,
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+ "dropout": 0.1,
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+ "early_stopping": true,
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+ "encoder_layerdrop": 0.05,
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+ "encoder_layers": 12,
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+ "gradient_checkpointing": false,
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+ "init_std": 0.02,
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+ "is_encoder_decoder": true,
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+ "max_length": 200,
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+ "max_position_embeddings": 1024,
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+ "model_type": "m2m_100",
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+ "num_beams": 5,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 1,
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+ "scale_embedding": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.11.0.dev0",
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+ "use_cache": true,
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+ "vocab_size": 128112
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+ }
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