belisards/nlabmm_final

README.md

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+---
+license: mit
+base_model: neuralmind/bert-large-portuguese-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- recall
+- precision
+model-index:
+- name: final
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# final
+
+This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3507
+- Accuracy: 0.8945
+- F1: 0.8863
+- Recall: 0.8760
+- Precision: 0.8968
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 5151
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
+| 0.485         | 0.9756 | 80   | 0.3916          | 0.8182   | 0.7984 | 0.7674 | 0.8319    |
+| 0.3395        | 1.9512 | 160  | 0.3039          | 0.8764   | 0.8547 | 0.7752 | 0.9524    |
+| 0.2139        | 2.9268 | 240  | 0.3122          | 0.8691   | 0.8548 | 0.8217 | 0.8908    |
+| 0.084         | 3.9024 | 320  | 0.3507          | 0.8945   | 0.8863 | 0.8760 | 0.8968    |
+| 0.058         | 4.8780 | 400  | 0.5087          | 0.8727   | 0.8571 | 0.8140 | 0.9052    |
+| 0.0389        | 5.8537 | 480  | 0.4579          | 0.8982   | 0.888  | 0.8605 | 0.9174    |
+| 0.0264        | 6.8293 | 560  | 0.5052          | 0.8873   | 0.8765 | 0.8527 | 0.9016    |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "neuralmind/bert-large-portuguese-cased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "output_past": true,
+  "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 29794
+}

model.safetensors

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+size 1337640872

training_args.bin

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+size 5240