End of training

README.md

@@ -0,0 +1,85 @@
+---
+base_model: aubmindlab/bert-base-arabertv2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: Improved-Arabert-twitter-sentiment-No-dropout
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# Improved-Arabert-twitter-sentiment-No-dropout
+
+This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5434
+- Accuracy: 0.9
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.5764        | 0.55  | 50   | 0.4925          | 0.79     |
+| 0.3357        | 1.1   | 100  | 0.3094          | 0.88     |
+| 0.2183        | 1.65  | 150  | 0.2971          | 0.87     |
+| 0.2042        | 2.2   | 200  | 0.3013          | 0.89     |
+| 0.1258        | 2.75  | 250  | 0.3038          | 0.9      |
+| 0.1359        | 3.3   | 300  | 0.3114          | 0.89     |
+| 0.0893        | 3.85  | 350  | 0.3108          | 0.91     |
+| 0.0816        | 4.4   | 400  | 0.3569          | 0.9      |
+| 0.071         | 4.95  | 450  | 0.3574          | 0.9      |
+| 0.1043        | 5.49  | 500  | 0.4332          | 0.89     |
+| 0.0407        | 6.04  | 550  | 0.4232          | 0.9      |
+| 0.0378        | 6.59  | 600  | 0.4273          | 0.91     |
+| 0.0341        | 7.14  | 650  | 0.4671          | 0.91     |
+| 0.0226        | 7.69  | 700  | 0.5174          | 0.9      |
+| 0.0215        | 8.24  | 750  | 0.4786          | 0.89     |
+| 0.0329        | 8.79  | 800  | 0.4853          | 0.9      |
+| 0.021         | 9.34  | 850  | 0.5430          | 0.9      |
+| 0.0219        | 9.89  | 900  | 0.5510          | 0.89     |
+| 0.0154        | 10.44 | 950  | 0.5518          | 0.9      |
+| 0.0119        | 10.99 | 1000 | 0.5473          | 0.9      |
+| 0.0108        | 11.54 | 1050 | 0.5285          | 0.9      |
+| 0.0138        | 12.09 | 1100 | 0.5239          | 0.91     |
+| 0.0133        | 12.64 | 1150 | 0.5584          | 0.89     |
+| 0.0121        | 13.19 | 1200 | 0.5334          | 0.9      |
+| 0.0063        | 13.74 | 1250 | 0.5325          | 0.91     |
+| 0.0061        | 14.29 | 1300 | 0.5429          | 0.9      |
+| 0.0105        | 14.84 | 1350 | 0.5434          | 0.9      |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.7
+- Tokenizers 0.14.1

config.json

@@ -8,16 +8,8 @@
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.1,
   "hidden_size": 768,
-  "id2label": {
-    "0": "Negative",
-    "1": "Positive"
-  },
   "initializer_range": 0.02,
   "intermediate_size": 3072,
-  "label2id": {
-    "Negative": 0,
-    "Positive": 1
-  },
   "layer_norm_eps": 1e-12,
   "max_position_embeddings": 512,
   "model_type": "bert",
@@ -25,6 +17,7 @@
   "num_hidden_layers": 12,
   "pad_token_id": 0,
   "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
   "torch_dtype": "float32",
   "transformers_version": "4.34.1",
   "type_vocab_size": 2,