End of training

README.md

@@ -1,199 +1,93 @@
 ---
-library_name: transformers
-tags: []
+base_model: Anwaarma/Improved-Arabert-twitter-sentiment2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: robust-arabert
+  results: []
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
-
-### Model Description
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-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
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-## Uses
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-## How to Get Started with the Model
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-Use the code below to get started with the model.
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-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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+<!-- 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. -->
+
+# robust-arabert
+
+This model is a fine-tuned version of [Anwaarma/Improved-Arabert-twitter-sentiment2](https://huggingface.co/Anwaarma/Improved-Arabert-twitter-sentiment2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2072
+- Accuracy: 0.94
+
+## 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        | 0.0546 | 50   | 0.2677          | 0.91     |
+| No log        | 0.1092 | 100  | 0.2432          | 0.93     |
+| No log        | 0.1638 | 150  | 0.3328          | 0.91     |
+| No log        | 0.2183 | 200  | 0.2894          | 0.92     |
+| No log        | 0.2729 | 250  | 0.3008          | 0.91     |
+| No log        | 0.3275 | 300  | 0.1951          | 0.93     |
+| No log        | 0.3821 | 350  | 0.2176          | 0.94     |
+| No log        | 0.4367 | 400  | 0.2291          | 0.95     |
+| No log        | 0.4913 | 450  | 0.2678          | 0.93     |
+| 0.2068        | 0.5459 | 500  | 0.2975          | 0.9      |
+| 0.2068        | 0.6004 | 550  | 0.2245          | 0.92     |
+| 0.2068        | 0.6550 | 600  | 0.2014          | 0.94     |
+| 0.2068        | 0.7096 | 650  | 0.2189          | 0.93     |
+| 0.2068        | 0.7642 | 700  | 0.2272          | 0.94     |
+| 0.2068        | 0.8188 | 750  | 0.2148          | 0.92     |
+| 0.2068        | 0.8734 | 800  | 0.2082          | 0.94     |
+| 0.2068        | 0.9279 | 850  | 0.1869          | 0.93     |
+| 0.2068        | 0.9825 | 900  | 0.2166          | 0.95     |
+| 0.2068        | 1.0371 | 950  | 0.2095          | 0.94     |
+| 0.1852        | 1.0917 | 1000 | 0.2948          | 0.92     |
+| 0.1852        | 1.1463 | 1050 | 0.2586          | 0.93     |
+| 0.1852        | 1.2009 | 1100 | 0.2669          | 0.93     |
+| 0.1852        | 1.2555 | 1150 | 0.2635          | 0.94     |
+| 0.1852        | 1.3100 | 1200 | 0.2600          | 0.94     |
+| 0.1852        | 1.3646 | 1250 | 0.2290          | 0.95     |
+| 0.1852        | 1.4192 | 1300 | 0.2248          | 0.95     |
+| 0.1852        | 1.4738 | 1350 | 0.1840          | 0.96     |
+| 0.1852        | 1.5284 | 1400 | 0.2366          | 0.95     |
+| 0.1852        | 1.5830 | 1450 | 0.2322          | 0.95     |
+| 0.1137        | 1.6376 | 1500 | 0.1797          | 0.96     |
+| 0.1137        | 1.6921 | 1550 | 0.1662          | 0.96     |
+| 0.1137        | 1.7467 | 1600 | 0.1762          | 0.96     |
+| 0.1137        | 1.8013 | 1650 | 0.1508          | 0.96     |
+| 0.1137        | 1.8559 | 1700 | 0.1996          | 0.95     |
+| 0.1137        | 1.9105 | 1750 | 0.2072          | 0.94     |
+
+
+### Framework versions
+
+- Transformers 4.42.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

@@ -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",

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