End of training

README.md

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+---
+license: apache-2.0
+base_model: HooshvareLab/bert-fa-base-uncased-clf-persiannews
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+model-index:
+- name: uncased-clf-persiannews_v1
+  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. -->
+
+# uncased-clf-persiannews_v1
+
+This model is a fine-tuned version of [HooshvareLab/bert-fa-base-uncased-clf-persiannews](https://huggingface.co/HooshvareLab/bert-fa-base-uncased-clf-persiannews) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.4385
+- Accuracy: 0.6459
+- F1: 0.6461
+- Precision: 0.6470
+
+## 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-06
+- 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 | F1     | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
+| No log        | 1.0   | 221  | 1.0855          | 0.6277   | 0.6263 | 0.6472    |
+| No log        | 2.0   | 442  | 1.0924          | 0.6549   | 0.6545 | 0.6598    |
+| 0.4554        | 3.0   | 663  | 1.1278          | 0.6583   | 0.6570 | 0.6609    |
+| 0.4554        | 4.0   | 884  | 1.2085          | 0.6481   | 0.6488 | 0.6559    |
+| 0.2653        | 5.0   | 1105 | 1.2614          | 0.6481   | 0.6487 | 0.6498    |
+| 0.2653        | 6.0   | 1326 | 1.3392          | 0.6402   | 0.6371 | 0.6433    |
+| 0.1817        | 7.0   | 1547 | 1.3692          | 0.6549   | 0.6543 | 0.6572    |
+| 0.1817        | 8.0   | 1768 | 1.4216          | 0.6425   | 0.6419 | 0.6424    |
+| 0.1817        | 9.0   | 1989 | 1.4325          | 0.6549   | 0.6551 | 0.6555    |
+| 0.1334        | 10.0  | 2210 | 1.4385          | 0.6459   | 0.6461 | 0.6470    |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "HooshvareLab/bert-fa-base-uncased-clf-persiannews",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "finetuning_task": "persiannews",
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "b2c",
+    "1": "adsl/sales",
+    "2": "b2b/res",
+    "3": "b2b/ent"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "adsl/sales": 1,
+    "b2b/ent": 3,
+    "b2b/res": 2,
+    "b2c": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.38.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 100000
+}

model.safetensors

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runs/Mar12_08-42-05_9a3446f3941f/events.out.tfevents.1710232926.9a3446f3941f.1243.0

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runs/Mar12_09-11-22_9a3446f3941f/events.out.tfevents.1710234682.9a3446f3941f.1243.1

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special_tokens_map.json

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+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+  "added_tokens_decoder": {
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+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
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+  "mask_token": "[MASK]",
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+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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