End of training

README.md

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+---
+license: apache-2.0
+base_model: dicta-il/BEREL_2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: my_awesome_model
+  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. -->
+
+# my_awesome_model
+
+This model is a fine-tuned version of [dicta-il/BEREL_2.0](https://huggingface.co/dicta-il/BEREL_2.0) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1927
+- Accuracy: 0.9507
+
+## 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: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2694        | 1.0   | 537  | 0.1761          | 0.9409   |
+| 0.0922        | 2.0   | 1074 | 0.1927          | 0.9507   |
+
+
+### Framework versions
+
+- Transformers 4.33.0
+- Pytorch 2.0.0
+- Datasets 2.1.0
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "dicta-il/BEREL_2.0",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "\u05d0\u05d5\u05e8\u05d7 \u05d7\u05d9\u05d9\u05dd",
+    "1": "\u05d9\u05d5\u05e8\u05d4 \u05d3\u05e2\u05d4",
+    "2": "\u05d7\u05e9\u05df \u05de\u05e9\u05e4\u05d8"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "\u05d0\u05d5\u05e8\u05d7 \u05d7\u05d9\u05d9\u05dd": 0,
+    "\u05d7\u05e9\u05df \u05de\u05e9\u05e4\u05d8": 2,
+    "\u05d9\u05d5\u05e8\u05d4 \u05d3\u05e2\u05d4": 1
+  },
+  "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",
+  "rabbinic": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.33.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 128000
+}

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:024a83c0c7dc380955f0565597d560b1cff0ae0c711ca460758c949589c02443
+size 737458993

special_tokens_map.json

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

tokenizer_config.json

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+{
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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+size 4027