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alionder
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acer_nitro_bert_turk

Text Classification
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bert
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Files changed (6) hide show
  1. README.md +20 -15
  2. config.json +13 -7
  3. model.safetensors +2 -2
  4. runs/Jan03_16-07-29_8786bb016a7d/events.out.tfevents.1704298050.8786bb016a7d.459.0 +3 -0
  5. runs/Jan03_16-07-29_8786bb016a7d/events.out.tfevents.1704298289.8786bb016a7d.459.1 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -18,10 +18,10 @@ should probably proofread and complete it, then remove this comment. -->
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  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.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8557
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- - F1: 0.5
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- - Roc Auc: 0.6286
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- - Accuracy: 0.0
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  ## Model description
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@@ -46,22 +46,27 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 5
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:---:|:-------:|:--------:|
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- | No log | 1.0 | 8 | 0.6628 | 0.5 | 0.6286 | 0.0 |
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- | No log | 2.0 | 16 | 0.7666 | 0.5 | 0.6286 | 0.0 |
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- | No log | 3.0 | 24 | 0.8261 | 0.5 | 0.6286 | 0.0 |
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- | No log | 4.0 | 32 | 0.8484 | 0.5 | 0.6286 | 0.0 |
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- | No log | 5.0 | 40 | 0.8557 | 0.5 | 0.6286 | 0.0 |
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.36.0
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- - Pytorch 2.1.0+cu118
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- - Datasets 2.15.0
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  - Tokenizers 0.15.0
 
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  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.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3791
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+ - F1: 0.8532
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+ - Roc Auc: 0.9236
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+ - Accuracy: 0.7108
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 10
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | No log | 1.0 | 166 | 0.3705 | 0.8426 | 0.9139 | 0.7229 |
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+ | No log | 2.0 | 332 | 0.3450 | 0.8584 | 0.9380 | 0.7470 |
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+ | No log | 3.0 | 498 | 0.3661 | 0.8491 | 0.9128 | 0.7108 |
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+ | 0.0532 | 4.0 | 664 | 0.3745 | 0.8558 | 0.9213 | 0.7229 |
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+ | 0.0532 | 5.0 | 830 | 0.3598 | 0.8571 | 0.9249 | 0.7349 |
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+ | 0.0532 | 6.0 | 996 | 0.3747 | 0.8571 | 0.9249 | 0.7229 |
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+ | 0.0219 | 7.0 | 1162 | 0.3540 | 0.8624 | 0.9297 | 0.7349 |
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+ | 0.0219 | 8.0 | 1328 | 0.3761 | 0.8584 | 0.9285 | 0.7229 |
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+ | 0.0219 | 9.0 | 1494 | 0.3836 | 0.8493 | 0.9223 | 0.7108 |
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+ | 0.0108 | 10.0 | 1660 | 0.3791 | 0.8532 | 0.9236 | 0.7108 |
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  ### Framework versions
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+ - Transformers 4.36.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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  - Tokenizers 0.15.0
config.json CHANGED
@@ -9,16 +9,22 @@
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  "hidden_dropout_prob": 0.1,
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  "hidden_size": 768,
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  "id2label": {
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- "0": "ram_agirlik",
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- "1": "ekran_karti_agirlik",
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- "2": "pil_agirlik"
 
 
 
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  },
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  "initializer_range": 0.02,
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  "intermediate_size": 3072,
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  "label2id": {
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- "ekran_karti_agirlik": 1,
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- "pil_agirlik": 2,
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- "ram_agirlik": 0
 
 
 
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  },
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  "layer_norm_eps": 1e-12,
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  "max_position_embeddings": 512,
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  "position_embedding_type": "absolute",
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  "problem_type": "multi_label_classification",
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  "torch_dtype": "float32",
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- "transformers_version": "4.36.0",
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  "type_vocab_size": 2,
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  "use_cache": true,
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  "vocab_size": 32000
 
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  "hidden_dropout_prob": 0.1,
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  "hidden_size": 768,
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  "id2label": {
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+ "0": "i\u015flemci",
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+ "1": "ekran_karti",
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+ "2": "batarya",
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+ "3": "ram",
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+ "4": "ssd",
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+ "5": "fiyat"
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  },
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  "initializer_range": 0.02,
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  "intermediate_size": 3072,
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  "label2id": {
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+ "batarya": 2,
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+ "ekran_karti": 1,
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+ "fiyat": 5,
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+ "i\u015flemci": 0,
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+ "ram": 3,
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+ "ssd": 4
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  },
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  "layer_norm_eps": 1e-12,
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  "max_position_embeddings": 512,
 
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  "position_embedding_type": "absolute",
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  "problem_type": "multi_label_classification",
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  "torch_dtype": "float32",
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+ "transformers_version": "4.36.2",
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  "type_vocab_size": 2,
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  "use_cache": true,
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  "vocab_size": 32000
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