shawhin/distilbert-base-uncased-lora-text-classification

README.md

@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.0259
-- Accuracy: {'accuracy': 0.892}
+- Loss: 1.0099
+- Accuracy: {'accuracy': 0.888}
 
 ## Model description
 
@@ -49,21 +49,21 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy            |
 |:-------------:|:-----:|:----:|:---------------:|:-------------------:|
-| No log        | 1.0   | 250  | 0.3888          | {'accuracy': 0.873} |
-| 0.4297        | 2.0   | 500  | 0.4399          | {'accuracy': 0.883} |
-| 0.4297        | 3.0   | 750  | 0.5721          | {'accuracy': 0.879} |
-| 0.2055        | 4.0   | 1000 | 0.6730          | {'accuracy': 0.886} |
-| 0.2055        | 5.0   | 1250 | 0.8363          | {'accuracy': 0.878} |
-| 0.0685        | 6.0   | 1500 | 0.9247          | {'accuracy': 0.882} |
-| 0.0685        | 7.0   | 1750 | 0.9256          | {'accuracy': 0.887} |
-| 0.0198        | 8.0   | 2000 | 1.0427          | {'accuracy': 0.891} |
-| 0.0198        | 9.0   | 2250 | 1.0151          | {'accuracy': 0.892} |
-| 0.0044        | 10.0  | 2500 | 1.0259          | {'accuracy': 0.892} |
+| No log        | 1.0   | 250  | 0.3473          | {'accuracy': 0.874} |
+| 0.4088        | 2.0   | 500  | 0.5087          | {'accuracy': 0.873} |
+| 0.4088        | 3.0   | 750  | 0.6246          | {'accuracy': 0.866} |
+| 0.2221        | 4.0   | 1000 | 0.7013          | {'accuracy': 0.887} |
+| 0.2221        | 5.0   | 1250 | 0.7331          | {'accuracy': 0.876} |
+| 0.1013        | 6.0   | 1500 | 0.8383          | {'accuracy': 0.88}  |
+| 0.1013        | 7.0   | 1750 | 0.8908          | {'accuracy': 0.886} |
+| 0.0269        | 8.0   | 2000 | 1.0219          | {'accuracy': 0.884} |
+| 0.0269        | 9.0   | 2250 | 1.0187          | {'accuracy': 0.878} |
+| 0.0102        | 10.0  | 2500 | 1.0099          | {'accuracy': 0.888} |
 
 
 ### Framework versions
 
-- Transformers 4.35.2
-- Pytorch 2.1.0+cu118
-- Datasets 2.15.0
-- Tokenizers 0.15.0
+- Transformers 4.35.0
+- Pytorch 2.0.0
+- Datasets 2.1.0
+- Tokenizers 0.14.1

adapter_model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:93fee39f278072caa0fc53daf12a363d1f45729037eb3599009028bac90f747a
+oid sha256:2c79458aecec0d407b194bac6372bc86827a709431a0fafef38ae6cc90320b2a
 size 2518104

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eeaaa27e323aa3ae43bdd2468620438087a7d1536138b2ec127cb0f5ffef6d72
+size 270352728

runs/Nov24_07-33-15_2a6580ebb096/events.out.tfevents.1700811201.2a6580ebb096.47.0

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:96161a9b174108e19fa8aeaaf722988ef91db9a2a0be4dd843e349b1fcd3d3a4
+size 8171

training_args.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0176eb10a6b4d093ff9a16c0a6b910860f0446bcc66fce6c035b3799ef5cf0a0
-size 4664
+oid sha256:0eeddfbe17f1f8bf305382d07e7abae2fede9f617ad00093c9cd37afc193418a
+size 4219