End of training

README.md

@@ -1,6 +1,6 @@
 ---
 license: mit
-base_model: microsoft/deberta-v3-large
+base_model: bobbyw/deberta-v3-large_v1_no_entities_with_context
 tags:
 - generated_from_trainer
 metrics:
@@ -18,9 +18,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 # deberta-v3-large_v1_no_entities_with_context
 
-This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset.
+This model is a fine-tuned version of [bobbyw/deberta-v3-large_v1_no_entities_with_context](https://huggingface.co/bobbyw/deberta-v3-large_v1_no_entities_with_context) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0256
+- Loss: 0.0257
 - Accuracy: 0.0045
 - F1: 0.0090
 - Precision: 0.0045
@@ -45,8 +45,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0002
-- train_batch_size: 2
-- eval_batch_size: 2
+- train_batch_size: 3
+- eval_batch_size: 3
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -56,10 +56,10 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Rate   |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
-| 0.0438        | 1.0   | 809  | 0.0270          | 0.0045   | 0.0090 | 0.0045    | 1.0    | 0.0002 |
-| 0.0306        | 2.0   | 1618 | 0.0265          | 0.0045   | 0.0090 | 0.0045    | 1.0    | 0.0001 |
-| 0.0323        | 3.0   | 2427 | 0.0255          | 0.0045   | 0.0090 | 0.0045    | 1.0    | 5e-05  |
-| 0.0298        | 4.0   | 3236 | 0.0256          | 0.0045   | 0.0090 | 0.0045    | 1.0    | 0.0    |
+| 0.0323        | 1.0   | 540  | 0.0261          | 0.0045   | 0.0090 | 0.0045    | 1.0    | 0.0002 |
+| 0.0306        | 2.0   | 1080 | 0.0263          | 0.0045   | 0.0090 | 0.0045    | 1.0    | 0.0001 |
+| 0.0318        | 3.0   | 1620 | 0.0258          | 0.0045   | 0.0090 | 0.0045    | 1.0    | 5e-05  |
+| 0.0301        | 4.0   | 2160 | 0.0257          | 0.0045   | 0.0090 | 0.0045    | 1.0    | 0.0    |
 
 
 ### Framework versions