Sentiment-Classification

README.md

@@ -3,9 +3,9 @@ license: apache-2.0
 library_name: peft
 tags:
 - generated_from_trainer
-base_model: distilbert-base-uncased
 metrics:
 - accuracy
+base_model: distilbert-base-uncased
 model-index:
 - name: distilbert-base-uncased-lora-text-classification
   results: []
@@ -18,8 +18,8 @@ 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: 0.4301
-- Accuracy: {'accuracy': 0.886}
+- Loss: 1.3518
+- Accuracy: {'accuracy': 0.892}
 
 ## Model description
 
@@ -44,20 +44,38 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 2
+- num_epochs: 20
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy            |
 |:-------------:|:-----:|:----:|:---------------:|:-------------------:|
-| No log        | 1.0   | 250  | 0.3356          | {'accuracy': 0.878} |
-| 0.4037        | 2.0   | 500  | 0.4301          | {'accuracy': 0.886} |
+| No log        | 1.0   | 250  | 0.5531          | {'accuracy': 0.844} |
+| 0.4257        | 2.0   | 500  | 0.3913          | {'accuracy': 0.888} |
+| 0.4257        | 3.0   | 750  | 0.6203          | {'accuracy': 0.865} |
+| 0.2247        | 4.0   | 1000 | 0.6630          | {'accuracy': 0.884} |
+| 0.2247        | 5.0   | 1250 | 0.8218          | {'accuracy': 0.885} |
+| 0.0802        | 6.0   | 1500 | 0.9760          | {'accuracy': 0.866} |
+| 0.0802        | 7.0   | 1750 | 0.9308          | {'accuracy': 0.882} |
+| 0.0458        | 8.0   | 2000 | 1.0010          | {'accuracy': 0.884} |
+| 0.0458        | 9.0   | 2250 | 1.2157          | {'accuracy': 0.884} |
+| 0.0263        | 10.0  | 2500 | 1.2556          | {'accuracy': 0.89}  |
+| 0.0263        | 11.0  | 2750 | 1.0911          | {'accuracy': 0.892} |
+| 0.0244        | 12.0  | 3000 | 1.2507          | {'accuracy': 0.884} |
+| 0.0244        | 13.0  | 3250 | 1.3437          | {'accuracy': 0.889} |
+| 0.0239        | 14.0  | 3500 | 1.1973          | {'accuracy': 0.893} |
+| 0.0239        | 15.0  | 3750 | 1.1784          | {'accuracy': 0.894} |
+| 0.0006        | 16.0  | 4000 | 1.2430          | {'accuracy': 0.892} |
+| 0.0006        | 17.0  | 4250 | 1.3177          | {'accuracy': 0.888} |
+| 0.0018        | 18.0  | 4500 | 1.3294          | {'accuracy': 0.893} |
+| 0.0018        | 19.0  | 4750 | 1.3637          | {'accuracy': 0.891} |
+| 0.0025        | 20.0  | 5000 | 1.3518          | {'accuracy': 0.892} |
 
 
 ### Framework versions
 
 - PEFT 0.10.0
-- Transformers 4.39.0
+- Transformers 4.38.2
 - Pytorch 2.2.1+cu121
 - Datasets 2.18.0
 - Tokenizers 0.15.2

adapter_config.json

@@ -1,7 +1,7 @@
 {
   "alpha_pattern": {},
   "auto_mapping": null,
-  "base_model_name_or_path": null,
+  "base_model_name_or_path": "distilbert-base-uncased",
   "bias": "none",
   "fan_in_fan_out": false,
   "inference_mode": true,

adapter_model.safetensors

@@ -1,3 +1,3 @@
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+size 2518104

runs/Mar25_13-56-22_1958dfbf93d9/events.out.tfevents.1711374983.1958dfbf93d9.3902.0

@@ -0,0 +1,3 @@
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+size 12545

training_args.bin

@@ -1,3 +1,3 @@
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 size 4984