Acc0.9001248439450686, F10.8994770073289435 , Augmented with Synonym-wordnet.csv, finetuned on ProsusAI/finbert

README.md

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+---
+base_model: ProsusAI/finbert
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: finbert_Synonym-wordnet
+  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. -->
+
+# finbert_Synonym-wordnet
+
+This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2734
+- Accuracy: 0.9236
+- F1: 0.9232
+- Precision: 0.9236
+- Recall: 0.9236
+
+## 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: 0.0001
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 1000
+- num_epochs: 25
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.7941        | 1.0   | 91   | 0.7038          | 0.7051   | 0.6964 | 0.7046    | 0.7051 |
+| 0.3785        | 2.0   | 182  | 0.2841          | 0.8939   | 0.8940 | 0.8942    | 0.8939 |
+| 0.213         | 3.0   | 273  | 0.2432          | 0.9080   | 0.9082 | 0.9106    | 0.9080 |
+| 0.1268        | 4.0   | 364  | 0.3080          | 0.8924   | 0.8927 | 0.8956    | 0.8924 |
+| 0.0851        | 5.0   | 455  | 0.2941          | 0.9173   | 0.9166 | 0.9183    | 0.9173 |
+| 0.0797        | 6.0   | 546  | 0.2734          | 0.9236   | 0.9232 | 0.9236    | 0.9236 |
+| 0.0651        | 7.0   | 637  | 0.3518          | 0.8970   | 0.8975 | 0.9029    | 0.8970 |
+| 0.0779        | 8.0   | 728  | 0.4189          | 0.8939   | 0.8942 | 0.9016    | 0.8939 |
+| 0.0923        | 9.0   | 819  | 0.3289          | 0.9126   | 0.9131 | 0.9152    | 0.9126 |
+| 0.087         | 10.0  | 910  | 0.3797          | 0.9048   | 0.9047 | 0.9075    | 0.9048 |
+| 0.0527        | 11.0  | 1001 | 0.3492          | 0.9048   | 0.9050 | 0.9058    | 0.9048 |
+
+
+### Framework versions
+
+- Transformers 4.37.0
+- Pytorch 2.1.2
+- Datasets 2.1.0
+- Tokenizers 0.15.1

config.json

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+{
+  "_name_or_path": "ProsusAI/finbert",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "positive",
+    "1": "negative",
+    "2": "neutral"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "negative": 1,
+    "neutral": 2,
+    "positive": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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+oid sha256:f352b4659459133201d5adb3c5558a4aa235fc02c19168fb8dc58f070e0b6b6b
+size 437961724

training_args.bin

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