End of training

README.md

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+---
+base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: fine-tuned-twitter-roberta-base-sentiment-latest
+  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. -->
+
+# fine-tuned-twitter-roberta-base-sentiment-latest
+
+This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3062
+- Accuracy: {'accuracy': 0.8868131868131868}
+- F1score: {'f1': 0.88247351021472}
+
+## 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-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy                         | F1score                    |
+|:-------------:|:------:|:----:|:---------------:|:--------------------------------:|:--------------------------:|
+| 0.461         | 0.2443 | 500  | 0.3381          | {'accuracy': 0.8565934065934065} | {'f1': 0.8483856477235431} |
+| 0.3702        | 0.4885 | 1000 | 0.3378          | {'accuracy': 0.865934065934066}  | {'f1': 0.8655309886906097} |
+| 0.3574        | 0.7328 | 1500 | 0.2971          | {'accuracy': 0.8714285714285714} | {'f1': 0.8709435986031107} |
+| 0.3358        | 0.9770 | 2000 | 0.3062          | {'accuracy': 0.8868131868131868} | {'f1': 0.88247351021472}   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "cardiffnlp/twitter-roberta-base-sentiment-latest",
+  "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": "negative",
+    "1": "neutral",
+    "2": "positive"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "negative": 0,
+    "neutral": 1,
+    "positive": 2
+  },
+  "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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+size 498615900

runs/Jun08_06-01-03_564f9400c222/events.out.tfevents.1717826484.564f9400c222.233.0

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training_args.bin

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