Add new CrossEncoder model

README.md

@@ -147,8 +147,8 @@ You can finetune this model on your own dataset.
 #### Non-Default Hyperparameters
 
 - `eval_strategy`: steps
-- `per_device_train_batch_size`: 32
-- `per_device_eval_batch_size`: 32
+- `per_device_train_batch_size`: 64
+- `per_device_eval_batch_size`: 64
 - `learning_rate`: 1e-05
 - `num_train_epochs`: 1
 - `warmup_steps`: 10283
@@ -162,8 +162,8 @@ You can finetune this model on your own dataset.
 - `do_predict`: False
 - `eval_strategy`: steps
 - `prediction_loss_only`: True
-- `per_device_train_batch_size`: 32
-- `per_device_eval_batch_size`: 32
+- `per_device_train_batch_size`: 64
+- `per_device_eval_batch_size`: 64
 - `per_gpu_train_batch_size`: None
 - `per_gpu_eval_batch_size`: None
 - `gradient_accumulation_steps`: 1
@@ -280,14 +280,13 @@ You can finetune this model on your own dataset.
 </details>
 
 ### Training Logs
-| Epoch  | Step | Training Loss | Validation Loss |
-|:------:|:----:|:-------------:|:---------------:|
-| 0.1556 | 500  | 0.2842        | 0.1468          |
-| 0.3111 | 1000 | 0.1083        | 0.0741          |
-| 0.1556 | 500  | 0.0652        | 0.0457          |
-| 0.3111 | 1000 | 0.0303        | 0.0189          |
-| 0.4667 | 1500 | 0.0157        | 0.0357          |
+| Epoch      | Step     | Training Loss | Validation Loss |
+|:----------:|:--------:|:-------------:|:---------------:|
+| 0.3111     | 500      | 0.0082        | 0.0072          |
+| **0.6223** | **1000** | **0.0043**    | **0.0027**      |
+| 0.9334     | 1500     | 0.0041        | 0.0388          |
 
+* The bold row denotes the saved checkpoint.
 
 ### Framework Versions
 - Python: 3.12.11