Multilingual-Perspectivist-NLU/irony_pt_Brazil

README.md

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+---
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: irony_pt_Brazil
+  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. -->
+
+# irony_pt_Brazil
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0033
+- Accuracy: 0.6463
+- Precision: 0.44
+- Recall: 0.5739
+- F1: 0.4981
+
+## 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: 5e-06
+- train_batch_size: 16
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.0043        | 1.0   | 71   | 0.0042          | 0.5745   | 0.3448    | 0.4348 | 0.3846 |
+| 0.0043        | 2.0   | 142  | 0.0041          | 0.5266   | 0.3562    | 0.6783 | 0.4671 |
+| 0.0039        | 3.0   | 213  | 0.0039          | 0.5266   | 0.3562    | 0.6783 | 0.4671 |
+| 0.004         | 4.0   | 284  | 0.0038          | 0.6170   | 0.4110    | 0.5826 | 0.4820 |
+| 0.0036        | 5.0   | 355  | 0.0035          | 0.6516   | 0.4452    | 0.5652 | 0.4981 |
+| 0.0035        | 6.0   | 426  | 0.0036          | 0.4973   | 0.3630    | 0.8522 | 0.5091 |
+| 0.0031        | 7.0   | 497  | 0.0033          | 0.5904   | 0.4156    | 0.8348 | 0.5549 |
+| 0.0027        | 8.0   | 568  | 0.0033          | 0.6543   | 0.4460    | 0.5391 | 0.4882 |
+| 0.0027        | 9.0   | 639  | 0.0031          | 0.6144   | 0.4257    | 0.7478 | 0.5426 |
+| 0.0023        | 10.0  | 710  | 0.0029          | 0.6303   | 0.4388    | 0.7478 | 0.5531 |
+| 0.0021        | 11.0  | 781  | 0.0031          | 0.6383   | 0.4348    | 0.6087 | 0.5072 |
+| 0.0018        | 12.0  | 852  | 0.0033          | 0.6463   | 0.44      | 0.5739 | 0.4981 |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.5
+- Tokenizers 0.14.1

config.json

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+{
+  "_name_or_path": "roberta-base",
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.34.1",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

pytorch_model.bin

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training_args.bin

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