Multilingual-Perspectivist-NLU/irony_es_United_States

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_United_States
+  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_United_States
+
+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: 0.0041
+- Accuracy: 0.6530
+- Precision: 0.4709
+- Recall: 0.3716
+- F1: 0.4154
+
+## 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   | 124  | 0.0043          | 0.5266   | 0.3652    | 0.5780 | 0.4476 |
+| 0.0043        | 2.0   | 248  | 0.0043          | 0.4414   | 0.3553    | 0.8394 | 0.4993 |
+| 0.0043        | 3.0   | 372  | 0.0042          | 0.6377   | 0.4398    | 0.3349 | 0.3802 |
+| 0.0042        | 4.0   | 496  | 0.0041          | 0.4414   | 0.3513    | 0.8073 | 0.4896 |
+| 0.004         | 5.0   | 620  | 0.0040          | 0.4840   | 0.3676    | 0.7706 | 0.4978 |
+| 0.0036        | 6.0   | 744  | 0.0036          | 0.6499   | 0.4764    | 0.5550 | 0.5127 |
+| 0.0031        | 7.0   | 868  | 0.0040          | 0.5297   | 0.3959    | 0.7936 | 0.5282 |
+| 0.0024        | 8.0   | 992  | 0.0041          | 0.6530   | 0.4709    | 0.3716 | 0.4154 |
+
+
+### 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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