Training in progress, epoch 1

README.md

@@ -64,7 +64,7 @@ The model was trained and evaluated on the [`dair-ai/emotion`](https://huggingfa
 
 - **Total Samples:** 20,000
   - **Training Set:** 15,000 samples
-  - **Validation Set:** 3,000 samples
+  - **Validation Set:** 2,000 samples
   - **Test Set:** 2,000 samples
 - **Emotion Classes:** 6
   - **Joy:** 3,000 samples
@@ -104,18 +104,6 @@ The following hyperparameters were used during training:
 - **Gradient Accumulation Steps:** `2` (effectively simulating a batch size of `32`)
 - **Mixed Precision Training:** Enabled (Native AMP) if CUDA is available
 
-### Training Environment
-
-- **Framework Versions:**
-  - **Transformers:** `4.46.2`
-  - **PyTorch:** `2.5.1+cu118`
-  - **Datasets:** `3.1.0`
-  - **Tokenizers:** `0.20.3`
-- **Hardware:** 
-  - **GPU:** NVIDIA RTX 3080 (Replace with your actual GPU)
-  - **CPU:** 16-core Intel Xeon (Replace with your actual CPU)
-  - **Memory:** 64 GB RAM (Replace with your actual RAM)
-
 ### Optimization Strategies
 
 - **Mixed Precision Training:** Utilized PyTorch's Native AMP to accelerate training and reduce memory consumption when a CUDA-enabled GPU is available.
@@ -125,10 +113,7 @@ The following hyperparameters were used during training:
 
 ### Training Duration
 
-- **Total Training Time:** Approximately `2.40` minutes (Note: Adjust this based on your actual training run)
-- **Training Steps:** `1000` steps
-- **Training Throughput:** `7.14` steps per second
-
+- **Total Training Time:** Approximately `2.40` minutes
 ### Logging and Monitoring
 
 - **Logging Directory:** `./logs`
@@ -142,13 +127,3 @@ After training, the model achieved the following performance metrics:
 
 - **Validation Accuracy:** `93.10%`
 - **Test Accuracy:** `93.10%`
-
-*Note:* The identical validation and test accuracies suggest consistent performance across both datasets. It's recommended to further investigate to ensure data splits are correctly managed and to explore additional metrics for a more comprehensive evaluation.
-
-### Framework Versions
-
-- **Transformers:** `4.46.2`
-- **PyTorch:** `2.5.1+cu118`
-- **Datasets:** `3.1.0`
-- **Tokenizers:** `0.20.3`
-

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