🔄 Incremental label | Acc: 0.714, F1: 0.519

.gitignore

@@ -0,0 +1,13 @@
+# TradePulse ML - Artefacts à ignorer
+logs/
+*.pt
+*.pth
+*.bin
+checkpoints/
+runs/
+wandb/
+*.log
+__pycache__/
+*.pyc
+.DS_Store
+tmp_eval/

README.md

@@ -1,71 +1,62 @@
 ---
-base_model: yiyanghkust/finbert-tone
+language: en
+license: apache-2.0
 tags:
-- generated_from_trainer
-metrics:
-- accuracy
-- precision
-- recall
-- f1
-model-index:
-- name: tradepulse-finbert-sentiment
-  results: []
+- finance
+- sentiment-analysis
+- finbert
+- trading
+pipeline_tag: text-classification
 ---
 
-<!-- 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. -->
+# Bencode92/tradepulse-finbert-sentiment
 
-# tradepulse-finbert-sentiment
+## Description
+Fine-tuned FinBERT model for financial sentiment analysis in TradePulse.
 
-This model is a fine-tuned version of [yiyanghkust/finbert-tone](https://huggingface.co/yiyanghkust/finbert-tone) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 2.7144
-- Accuracy: 0.3846
-- Precision: 0.4462
-- Recall: 0.3846
-- F1: 0.4126
-- F1 Macro: 0.3258
-- Precision Macro: 0.3500
-- Recall Macro: 0.3056
+**Task**: Sentiment Classification  
+**Target Column**: `label`  
+**Labels**: ['negative', 'neutral', 'positive']
 
-## Model description
+## Performance
 
-More information needed
+*Last training: 2025-07-09 15:39*  
+*Dataset: `news_20250709.csv` (56 samples)*
 
-## Intended uses & limitations
+| Metric | Value |
+|--------|-------|
+| Loss | 1.6623 |
+| Accuracy | 0.7857 |
+| F1 Score | 0.7837 |
+| F1 Macro | 0.7837 |
+| Precision | 0.7934 |
+| Recall | 0.7857 |
 
-More information needed
+## Training Details
 
-## Training and evaluation data
+- **Base Model**: Bencode92/tradepulse-finbert-sentiment
+- **Training Mode**: Incremental
+- **Epochs**: 2
+- **Learning Rate**: 1e-05
+- **Batch Size**: 4
+- **Class Balancing**: None
 
-More information needed
+## Usage
 
-## Training procedure
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
-### Training hyperparameters
+tokenizer = AutoTokenizer.from_pretrained("Bencode92/tradepulse-finbert-sentiment")
+model = AutoModelForSequenceClassification.from_pretrained("Bencode92/tradepulse-finbert-sentiment")
 
-The following hyperparameters were used during training:
-- learning_rate: 2e-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
-- lr_scheduler_warmup_steps: 12
-- num_epochs: 3
+# Example prediction
+text = "Apple reported strong quarterly earnings beating expectations"
+inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
+outputs = model(**inputs)
+predictions = outputs.logits.softmax(dim=-1)
+```
 
-### Training results
+## Model Card Authors
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | F1 Macro | Precision Macro | Recall Macro |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:--------:|:---------------:|:------------:|
-| No log        | 1.0   | 7    | 5.3820          | 0.3077   | 0.3077    | 0.3077 | 0.3077 | 0.2222   | 0.2222          | 0.2222       |
-| 4.744         | 2.0   | 14   | 3.3730          | 0.3846   | 0.4462    | 0.3846 | 0.4126 | 0.3258   | 0.3500          | 0.3056       |
-| 1.0682        | 3.0   | 21   | 2.7144          | 0.3846   | 0.4462    | 0.3846 | 0.4126 | 0.3258   | 0.3500          | 0.3056       |
-
-
-### Framework versions
-
-- Transformers 4.41.0
-- Pytorch 2.7.1+cpu
-- Datasets 2.19.1
-- Tokenizers 0.19.1
+- TradePulse ML Team
+- Auto-generated on 2025-07-09 15:39:06

checkpoint-11/config.json

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+{
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+  "architectures": [
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+  ],
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+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "negative",
+    "1": "neutral",
+    "2": "positive"
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+  "intermediate_size": 3072,
+  "label2id": {
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+    "neutral": 1,
+    "positive": 2
+  },
+  "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": "4.41.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30873
+}

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checkpoint-11/tokenizer_config.json

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+}

checkpoint-11/trainer_state.json

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config.json

@@ -1,5 +1,5 @@
 {
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+  "_name_or_path": "Bencode92/tradepulse-finbert-sentiment",
   "architectures": [
     "BertForSequenceClassification"
   ],

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