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mehdie/fine_tuned_mBERT

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  1. README.md +73 -0
  2. config.json +40 -0
  3. model.safetensors +3 -0
  4. runs/Apr30_09-04-55_a256-a40-06.srv.aau.dk/events.out.tfevents.1714460696.a256-a40-06.srv.aau.dk.1177277.0 +3 -0
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  19. tokenizer.json +0 -0
  20. tokenizer_config.json +55 -0
  21. training_args.bin +3 -0
  22. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google-bert/bert-base-multilingual-cased
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: fine_tuned_mBERT
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+ results: []
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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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+ # fine_tuned_mBERT
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+
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+ This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1592
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+ - F1: 0.7805
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+ - F5: 0.8186
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+ - Precision: 0.6957
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+ - Recall: 0.8889
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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: 5e-05
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+ - train_batch_size: 256
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+ - eval_batch_size: 256
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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: 8
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | F5 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:|
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+ | No log | 1.0 | 6 | 0.3289 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 2.0 | 12 | 0.3095 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 3.0 | 18 | 0.2680 | 0.3636 | 0.2925 | 1.0 | 0.2222 |
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+ | No log | 4.0 | 24 | 0.2876 | 0.4 | 0.3424 | 0.7143 | 0.2778 |
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+ | No log | 5.0 | 30 | 0.2680 | 0.6087 | 0.6638 | 0.5 | 0.7778 |
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+ | No log | 6.0 | 36 | 0.2565 | 0.4615 | 0.4024 | 0.75 | 0.3333 |
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+ | No log | 7.0 | 42 | 0.2320 | 0.6341 | 0.6651 | 0.5652 | 0.7222 |
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+ | No log | 8.0 | 48 | 0.2251 | 0.6 | 0.5574 | 0.75 | 0.5 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.3.0a0+ebedce2
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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+ {
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+ "_name_or_path": "google-bert/bert-base-multilingual-cased",
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "classifier_dropout": null,
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+ "directionality": "bidi",
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "NO_MATCH",
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "pooler_fc_size": 768,
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+ "pooler_num_attention_heads": 12,
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+ "pooler_num_fc_layers": 3,
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+ "pooler_size_per_head": 128,
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+ "pooler_type": "first_token_transform",
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.38.2",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 119547
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