Multilingual-Perspectivist-NLU/irony_de_Germany

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_de_Germany
+  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_de_Germany
+
+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: 0.0040
+- Accuracy: 0.5332
+- Precision: 0.3392
+- Recall: 0.8
+- F1: 0.4764
+
+## 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   | 85   | 0.0043          | 0.6372   | 0.3533    | 0.4417 | 0.3926 |
+| 0.0041        | 2.0   | 170  | 0.0041          | 0.6571   | 0.3856    | 0.4917 | 0.4322 |
+| 0.0039        | 3.0   | 255  | 0.0039          | 0.5619   | 0.3274    | 0.6167 | 0.4277 |
+| 0.0035        | 4.0   | 340  | 0.0037          | 0.5951   | 0.3478    | 0.6    | 0.4404 |
+| 0.0033        | 5.0   | 425  | 0.0037          | 0.5885   | 0.3429    | 0.6    | 0.4364 |
+| 0.0026        | 6.0   | 510  | 0.0037          | 0.6128   | 0.3659    | 0.625  | 0.4615 |
+| 0.0025        | 7.0   | 595  | 0.0035          | 0.5177   | 0.3367    | 0.8417 | 0.4810 |
+| 0.0021        | 8.0   | 680  | 0.0036          | 0.5664   | 0.3504    | 0.7417 | 0.4759 |
+| 0.0013        | 9.0   | 765  | 0.0040          | 0.5332   | 0.3392    | 0.8    | 0.4764 |
+
+
+### 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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