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fine_tuned_mBERT

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morten-j/fine_tuned_mBERT

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  2. config.json +40 -0
  3. model.safetensors +3 -0
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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_bert
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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_bert
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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: 0.0784
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+ - F1: 0.8571
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+ - F5: 0.8730
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+ - Precision: 0.8182
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+ - Recall: 0.9
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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: 32
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+ - eval_batch_size: 32
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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: 10
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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 | 65 | 0.2314 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 2.0 | 130 | 0.2243 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 3.0 | 195 | 0.2556 | 0.2105 | 0.2193 | 0.1905 | 0.2353 |
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+ | No log | 4.0 | 260 | 0.2236 | 0.5 | 0.5627 | 0.3871 | 0.7059 |
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+ | No log | 5.0 | 325 | 0.2295 | 0.4545 | 0.3762 | 1.0 | 0.2941 |
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+ | No log | 6.0 | 390 | 0.2185 | 0.5 | 0.4313 | 0.8571 | 0.3529 |
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+ | No log | 7.0 | 455 | 0.2666 | 0.5366 | 0.5740 | 0.4583 | 0.6471 |
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+ | 0.1993 | 8.0 | 520 | 0.1813 | 0.6429 | 0.5942 | 0.8182 | 0.5294 |
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+ | 0.1993 | 9.0 | 585 | 0.2069 | 0.6452 | 0.6222 | 0.7143 | 0.5882 |
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+ | 0.1993 | 10.0 | 650 | 0.2014 | 0.6897 | 0.6470 | 0.8333 | 0.5882 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.1
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.17.0
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+ - Tokenizers 0.15.2
config.json ADDED
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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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+ "attention_probs_dropout_prob": 0.1,
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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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+ "1": "MATCH"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "MATCH": 1,
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+ "NO_MATCH": 0
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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": "4.38.1",
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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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+ }
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