Multilingual-Perspectivist-NLU/irony_en_United_Kingdom

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_en_United_Kingdom
+  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_en_United_Kingdom
+
+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: 0.0023
+- Accuracy: 0.6833
+- Precision: 0.4764
+- Recall: 0.7339
+- F1: 0.5778
+
+## 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   | 79   | 0.0042          | 0.5310   | 0.3612    | 0.7661 | 0.4910 |
+| 0.0043        | 2.0   | 158  | 0.0040          | 0.6595   | 0.4417    | 0.5806 | 0.5017 |
+| 0.0039        | 3.0   | 237  | 0.0034          | 0.6310   | 0.4188    | 0.6452 | 0.5079 |
+| 0.0033        | 4.0   | 316  | 0.0027          | 0.7286   | 0.5352    | 0.6129 | 0.5714 |
+| 0.0022        | 5.0   | 395  | 0.0024          | 0.5833   | 0.4066    | 0.8952 | 0.5592 |
+| 0.0015        | 6.0   | 474  | 0.0022          | 0.7357   | 0.5474    | 0.6048 | 0.5747 |
+| 0.001         | 7.0   | 553  | 0.0022          | 0.7262   | 0.5302    | 0.6371 | 0.5788 |
+| 0.0005        | 8.0   | 632  | 0.0023          | 0.6833   | 0.4764    | 0.7339 | 0.5778 |
+
+
+### 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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