jessgomesgomez
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Commit
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Training complete
Browse files- README.md +8 -7
- config.json +10 -9
- model.safetensors +2 -2
- tokenizer.json +0 -0
- tokenizer_config.json +12 -14
- training_args.bin +1 -1
- vocab.txt +0 -0
README.md
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---
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-
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tags:
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- classification
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- generated_from_trainer
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@@ -15,10 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
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# clasificador-muchocine
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This model is a fine-tuned version of [
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It achieves the following results on the evaluation set:
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- Loss: 1.
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- Accuracy: 0.
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## Model description
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@@ -49,9 +50,9 @@ The following hyperparameters were used during training:
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 388 | 1.
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| 1.
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### Framework versions
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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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- classification
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- generated_from_trainer
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# clasificador-muchocine
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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 the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.5252
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- Accuracy: 0.3355
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 388 | 1.5330 | 0.3355 |
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| 1.5357 | 2.0 | 776 | 1.5317 | 0.3355 |
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| 1.5245 | 3.0 | 1164 | 1.5252 | 0.3355 |
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### Framework versions
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config.json
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{
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"_name_or_path": "
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"architectures": [
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"
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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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"
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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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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "
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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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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"summary_activation": "gelu",
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"summary_last_dropout": 0.1,
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"summary_type": "first",
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"summary_use_proj": true,
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"torch_dtype": "float32",
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"transformers_version": "4.40.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size":
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}
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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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},
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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": "4.40.2",
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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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}
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model.safetensors
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tokenizer.json
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tokenizer_config.json
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{
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"special": true
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"tokenize_chinese_chars": true,
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_lower_case": false,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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}
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training_args.bin
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vocab.txt
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