End of training

README.md

@@ -0,0 +1,84 @@
+---
+base_model: aubmindlab/bert-base-arabertv02-twitter
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: Improved-Arabert-twitter-sentiment2
+  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-sentiment2
+
+This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-base-arabertv02-twitter) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4308
+- Accuracy: 0.8759
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.07  | 50   | 0.4102          | 0.8130   |
+| No log        | 0.14  | 100  | 0.3141          | 0.8769   |
+| No log        | 0.21  | 150  | 0.2981          | 0.8806   |
+| No log        | 0.27  | 200  | 0.3297          | 0.8769   |
+| No log        | 0.34  | 250  | 0.2998          | 0.8796   |
+| No log        | 0.41  | 300  | 0.3312          | 0.8630   |
+| No log        | 0.48  | 350  | 0.3615          | 0.8491   |
+| No log        | 0.55  | 400  | 0.3695          | 0.8481   |
+| No log        | 0.62  | 450  | 0.3094          | 0.8778   |
+| 0.316         | 0.68  | 500  | 0.2784          | 0.8907   |
+| 0.316         | 0.75  | 550  | 0.3404          | 0.8759   |
+| 0.316         | 0.82  | 600  | 0.3045          | 0.8806   |
+| 0.316         | 0.89  | 650  | 0.3435          | 0.8731   |
+| 0.316         | 0.96  | 700  | 0.2849          | 0.9      |
+| 0.316         | 1.03  | 750  | 0.2846          | 0.8963   |
+| 0.316         | 1.1   | 800  | 0.3034          | 0.8926   |
+| 0.316         | 1.16  | 850  | 0.3801          | 0.8787   |
+| 0.316         | 1.23  | 900  | 0.3525          | 0.8898   |
+| 0.316         | 1.3   | 950  | 0.3388          | 0.8889   |
+| 0.2119        | 1.37  | 1000 | 0.3823          | 0.8843   |
+| 0.2119        | 1.44  | 1050 | 0.3621          | 0.8935   |
+| 0.2119        | 1.51  | 1100 | 0.4106          | 0.8843   |
+| 0.2119        | 1.58  | 1150 | 0.3820          | 0.8870   |
+| 0.2119        | 1.64  | 1200 | 0.3770          | 0.8796   |
+| 0.2119        | 1.71  | 1250 | 0.4199          | 0.8824   |
+| 0.2119        | 1.78  | 1300 | 0.4308          | 0.8759   |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.7
+- Tokenizers 0.14.1

config.json

@@ -1,7 +1,7 @@
 {
   "_name_or_path": "aubmindlab/bert-base-arabertv02-twitter",
   "architectures": [
-    "BertForMaskedLM"
+    "BertForSequenceClassification"
   ],
   "attention_probs_dropout_prob": 0.1,
   "classifier_dropout": null,
@@ -9,16 +9,8 @@
   "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",
@@ -26,6 +18,7 @@
   "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,

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