Multilingual-Perspectivist-NLU/irony_es_Mexico

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_es_Mexico
+  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_es_Mexico
+
+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: 0.0036
+- Accuracy: 0.6531
+- Precision: 0.5292
+- Recall: 0.5686
+- F1: 0.5482
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.0044        | 1.0   | 129  | 0.0042          | 0.5922   | 0.448     | 0.4392 | 0.4436 |
+| 0.0041        | 2.0   | 258  | 0.0041          | 0.5239   | 0.4238    | 0.7961 | 0.5531 |
+| 0.0039        | 3.0   | 387  | 0.0038          | 0.5864   | 0.4615    | 0.7059 | 0.5581 |
+| 0.0034        | 4.0   | 516  | 0.0034          | 0.5399   | 0.4362    | 0.8314 | 0.5722 |
+| 0.003         | 5.0   | 645  | 0.0032          | 0.6241   | 0.4944    | 0.6902 | 0.5761 |
+| 0.0023        | 6.0   | 774  | 0.0036          | 0.5733   | 0.4509    | 0.7020 | 0.5491 |
+| 0.0022        | 7.0   | 903  | 0.0036          | 0.6531   | 0.5292    | 0.5686 | 0.5482 |
+
+
+### 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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