End of training

README.md

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+---
+base_model: cardiffnlp/twitter-roberta-base-irony
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: twitter-roberta-base_3epoch
+  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. -->
+
+# twitter-roberta-base_3epoch
+
+This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-irony](https://huggingface.co/cardiffnlp/twitter-roberta-base-irony) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9201
+- Accuracy: 0.7723
+- F1: 0.5183
+- Precision: 0.6589
+- Recall: 0.4271
+- Precision Sarcastic: 0.6589
+- Recall Sarcastic: 0.4271
+- F1 Sarcastic: 0.5183
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
+| No log        | 1.0   | 174  | 0.6210          | 0.7248   | 0.1116 | 0.75      | 0.0603 | 0.75                | 0.0603           | 0.1116       |
+| No log        | 2.0   | 348  | 0.5732          | 0.7767   | 0.5016 | 0.6964    | 0.3920 | 0.6964              | 0.3920           | 0.5016       |
+| 0.3415        | 3.0   | 522  | 0.9201          | 0.7723   | 0.5183 | 0.6589    | 0.4271 | 0.6589              | 0.4271           | 0.5183       |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "cardiffnlp/twitter-roberta-base-irony",
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "non_irony",
+    "1": "irony"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "irony": 1,
+    "non_irony": 0
+  },
+  "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": "4.41.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

model.safetensors

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runs/May31_17-10-58_e05c0a46fc41/events.out.tfevents.1717175459.e05c0a46fc41.1080.69

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special_tokens_map.json

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+}

tokenizer_config.json

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+  "errors": "replace",
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+  "pad_token": "<pad>",
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+  "tokenizer_class": "RobertaTokenizer",
+  "trim_offsets": true,
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+}

training_args.bin

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