alperengozeten/turkish-emotion-model

README.md

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+---
+license: mit
+base_model: dbmdz/distilbert-base-turkish-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: results
+  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. -->
+
+# results
+
+This model is a fine-tuned version of [dbmdz/distilbert-base-turkish-cased](https://huggingface.co/dbmdz/distilbert-base-turkish-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1938
+- Accuracy: 0.9592
+
+## 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: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.9211        | 0.07  | 100  | 1.8456          | 0.3225   |
+| 1.6177        | 0.14  | 200  | 1.2261          | 0.5982   |
+| 0.8794        | 0.21  | 300  | 0.4865          | 0.8638   |
+| 0.428         | 0.27  | 400  | 0.3350          | 0.8991   |
+| 0.3189        | 0.34  | 500  | 0.2934          | 0.9128   |
+| 0.2869        | 0.41  | 600  | 0.2728          | 0.9219   |
+| 0.2776        | 0.48  | 700  | 0.2529          | 0.9267   |
+| 0.2334        | 0.55  | 800  | 0.2609          | 0.9303   |
+| 0.2314        | 0.62  | 900  | 0.2157          | 0.9369   |
+| 0.2381        | 0.69  | 1000 | 0.1924          | 0.9431   |
+| 0.2574        | 0.75  | 1100 | 0.2476          | 0.9260   |
+| 0.2068        | 0.82  | 1200 | 0.1919          | 0.9429   |
+| 0.241         | 0.89  | 1300 | 0.1865          | 0.9417   |
+| 0.1894        | 0.96  | 1400 | 0.2022          | 0.9453   |
+| 0.1791        | 1.03  | 1500 | 0.2078          | 0.9448   |
+| 0.1131        | 1.1   | 1600 | 0.1995          | 0.9493   |
+| 0.1082        | 1.17  | 1700 | 0.2074          | 0.9498   |
+| 0.1088        | 1.23  | 1800 | 0.2139          | 0.9467   |
+| 0.1123        | 1.3   | 1900 | 0.2086          | 0.9481   |
+| 0.1083        | 1.37  | 2000 | 0.1964          | 0.9498   |
+| 0.1318        | 1.44  | 2100 | 0.1872          | 0.9503   |
+| 0.1016        | 1.51  | 2200 | 0.2005          | 0.9486   |
+| 0.1415        | 1.58  | 2300 | 0.1918          | 0.9507   |
+| 0.1292        | 1.64  | 2400 | 0.1848          | 0.9520   |
+| 0.0939        | 1.71  | 2500 | 0.1870          | 0.9539   |
+| 0.1301        | 1.78  | 2600 | 0.1950          | 0.9525   |
+| 0.1415        | 1.85  | 2700 | 0.1955          | 0.9501   |
+| 0.1474        | 1.92  | 2800 | 0.1797          | 0.9556   |
+| 0.1169        | 1.99  | 2900 | 0.1767          | 0.9577   |
+| 0.0562        | 2.06  | 3000 | 0.1847          | 0.9563   |
+| 0.0653        | 2.12  | 3100 | 0.1839          | 0.9584   |
+| 0.0431        | 2.19  | 3200 | 0.1853          | 0.9565   |
+| 0.0289        | 2.26  | 3300 | 0.1922          | 0.9572   |
+| 0.0507        | 2.33  | 3400 | 0.1989          | 0.9582   |
+| 0.0475        | 2.4   | 3500 | 0.2009          | 0.9573   |
+| 0.0434        | 2.47  | 3600 | 0.1959          | 0.9580   |
+| 0.0479        | 2.54  | 3700 | 0.1942          | 0.9585   |
+| 0.0421        | 2.6   | 3800 | 0.1986          | 0.9578   |
+| 0.0496        | 2.67  | 3900 | 0.1947          | 0.9577   |
+| 0.0452        | 2.74  | 4000 | 0.1938          | 0.9594   |
+| 0.0329        | 2.81  | 4100 | 0.1936          | 0.9594   |
+| 0.0568        | 2.88  | 4200 | 0.1934          | 0.9584   |
+| 0.0441        | 2.95  | 4300 | 0.1938          | 0.9592   |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

config.json

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+{
+  "_name_or_path": "dbmdz/distilbert-base-turkish-cased",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "output_past": true,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": true,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.35.0",
+  "vocab_size": 32000
+}

model.safetensors

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training_args.bin

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