🔄 Incremental label | Acc: 0.950, F1: 0.965

README.md

@@ -6,6 +6,7 @@ tags:
 - sentiment-analysis
 - finbert
 - trading
+
 pipeline_tag: text-classification
 ---
 
@@ -20,17 +21,19 @@ Fine-tuned FinBERT model for financial sentiment analysis in TradePulse.
 
 ## Performance
 
-*Last training: 2025-07-24 14:46*  
-*Dataset: `news_20250724.csv` (27 samples)*
+*Last training: 2025-07-24 15:44*  
+*Dataset: `news_20250724.csv` (171 samples)*
 
 | Metric | Value |
 |--------|-------|
-| Loss | 0.1390 |
-| Accuracy | 1.0000 |
-| F1 Score | 1.0000 |
-| F1 Macro | 1.0000 |
-| Precision | 1.0000 |
-| Recall | 1.0000 |
+| Loss | 0.2699 |
+| Accuracy | 0.9535 |
+| F1 Score | 0.9535 |
+
+| F1 Macro | 0.9535 |
+
+| Precision | 0.9579 |
+| Recall | 0.9535 |
 
 ## Training Details
 
@@ -41,10 +44,12 @@ Fine-tuned FinBERT model for financial sentiment analysis in TradePulse.
 - **Batch Size**: 4
 - **Class Balancing**: None
 
+
 ## Usage
 
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
 
 tokenizer = AutoTokenizer.from_pretrained("Bencode92/tradepulse-finbert-sentiment")
 model = AutoModelForSequenceClassification.from_pretrained("Bencode92/tradepulse-finbert-sentiment")
@@ -53,10 +58,11 @@ model = AutoModelForSequenceClassification.from_pretrained("Bencode92/tradepulse
 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)
 ```
 
 ## Model Card Authors
 
 - TradePulse ML Team
-- Auto-generated on 2025-07-24 14:46:15
+- Auto-generated on 2025-07-24 15:44:30

{checkpoint-5 → checkpoint-32}/model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d9610a745670b14473c110be48706aede4781a83928fe1ca7704edc21d20b5f6
+oid sha256:0c790fd6e8d95e12a74a0f232817351992936b6aa478caf158acf325cd08cf87
 size 439039996

{checkpoint-5 → checkpoint-32}/trainer_state.json

@@ -1,31 +1,52 @@
 {
-  "best_metric": 1.0,
-  "best_model_checkpoint": "hf-sentiment-production/checkpoint-5",
+  "best_metric": 0.9534883720930233,
+  "best_model_checkpoint": "hf-sentiment-production/checkpoint-32",
   "epoch": 1.0,
   "eval_steps": 500,
-  "global_step": 5,
+  "global_step": 32,
   "is_hyper_param_search": false,
   "is_local_process_zero": true,
   "is_world_process_zero": true,
   "log_history": [
+    {
+      "epoch": 0.3125,
+      "grad_norm": 20.869625091552734,
+      "learning_rate": 3.125e-06,
+      "loss": 0.2232,
+      "step": 10
+    },
+    {
+      "epoch": 0.625,
+      "grad_norm": 24.07443618774414,
+      "learning_rate": 6.25e-06,
+      "loss": 0.142,
+      "step": 20
+    },
+    {
+      "epoch": 0.9375,
+      "grad_norm": 5.75204610824585,
+      "learning_rate": 9.375000000000001e-06,
+      "loss": 0.203,
+      "step": 30
+    },
     {
       "epoch": 1.0,
-      "eval_accuracy": 1.0,
-      "eval_f1": 1.0,
-      "eval_f1_macro": 1.0,
-      "eval_loss": 0.13897599279880524,
-      "eval_precision": 1.0,
-      "eval_precision_macro": 1.0,
-      "eval_recall": 1.0,
-      "eval_recall_macro": 1.0,
-      "eval_runtime": 3.9596,
-      "eval_samples_per_second": 1.768,
-      "eval_steps_per_second": 0.505,
-      "step": 5
+      "eval_accuracy": 0.9534883720930233,
+      "eval_f1": 0.9534883720930233,
+      "eval_f1_macro": 0.9666666666666667,
+      "eval_loss": 0.26990270614624023,
+      "eval_precision": 0.9579180509413068,
+      "eval_precision_macro": 0.9682539682539683,
+      "eval_recall": 0.9534883720930233,
+      "eval_recall_macro": 0.9682539682539683,
+      "eval_runtime": 23.8102,
+      "eval_samples_per_second": 1.806,
+      "eval_steps_per_second": 0.462,
+      "step": 32
     }
   ],
   "logging_steps": 10,
-  "max_steps": 10,
+  "max_steps": 64,
   "num_input_tokens_seen": 0,
   "num_train_epochs": 2,
   "save_steps": 500,
@@ -50,7 +71,7 @@
       "attributes": {}
     }
   },
-  "total_flos": 5262268354560.0,
+  "total_flos": 33678517469184.0,
   "train_batch_size": 4,
   "trial_name": null,
   "trial_params": null

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d9610a745670b14473c110be48706aede4781a83928fe1ca7704edc21d20b5f6
+oid sha256:0c790fd6e8d95e12a74a0f232817351992936b6aa478caf158acf325cd08cf87
 size 439039996

training_args.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7a73d72562f4cffef7c111bb7419e095d87df7c9b49e48b855a28e531bcf3d26
+oid sha256:0797cb80249f45aa53e3f7e5498774d0cda687d153caa26fca11f969aecb203d
 size 5521