alperengozeten/turkish-emotion-model

README.md

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+---
+license: mit
+base_model: dbmdz/bert-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/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3687
+- Accuracy: 0.9130
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.8572        | 0.14  | 200  | 1.4831          | 0.4714   |
+| 1.2551        | 0.27  | 400  | 0.9639          | 0.6684   |
+| 0.886         | 0.41  | 600  | 0.7681          | 0.7507   |
+| 0.7313        | 0.55  | 800  | 0.5526          | 0.8317   |
+| 0.5804        | 0.69  | 1000 | 0.5308          | 0.8312   |
+| 0.5407        | 0.82  | 1200 | 0.4486          | 0.8595   |
+| 0.502         | 0.96  | 1400 | 0.5216          | 0.8516   |
+| 0.3737        | 1.1   | 1600 | 0.4527          | 0.8763   |
+| 0.3367        | 1.23  | 1800 | 0.4716          | 0.8544   |
+| 0.3272        | 1.37  | 2000 | 0.3905          | 0.8862   |
+| 0.2988        | 1.51  | 2200 | 0.3661          | 0.8926   |
+| 0.298         | 1.64  | 2400 | 0.4301          | 0.8898   |
+| 0.2856        | 1.78  | 2600 | 0.3944          | 0.8943   |
+| 0.2832        | 1.92  | 2800 | 0.3608          | 0.8979   |
+| 0.2483        | 2.06  | 3000 | 0.3757          | 0.8987   |
+| 0.1699        | 2.19  | 3200 | 0.3802          | 0.9100   |
+| 0.1433        | 2.33  | 3400 | 0.4144          | 0.9114   |
+| 0.1826        | 2.47  | 3600 | 0.3533          | 0.9124   |
+| 0.159         | 2.6   | 3800 | 0.3708          | 0.9107   |
+| 0.1601        | 2.74  | 4000 | 0.3775          | 0.9118   |
+| 0.1442        | 2.88  | 4200 | 0.3687          | 0.9130   |
+
+
+### 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/bert-base-turkish-cased",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "attention_probs_dropout_prob": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dim": 3072,
+  "hidden_dropout_prob": 0.1,
+  "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,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 12,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.35.0",
+  "type_vocab_size": 2,
+  "vocab_size": 32000
+}

model.safetensors

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+size 442509060

training_args.bin

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