rwBK-sentiment-analysis-heBert

README.md

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+---
+base_model: avichr/heBERT_sentiment_analysis
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: heBERT_sentiment_analysis
+  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. -->
+
+# heBERT_sentiment_analysis
+
+This model is a fine-tuned version of [avichr/heBERT_sentiment_analysis](https://huggingface.co/avichr/heBERT_sentiment_analysis) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4046
+- Accuracy: 0.8563
+- F1: 0.8554
+- Precision: 0.8551
+- Recall: 0.8567
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 2.5497        | 0.0820 | 50   | 0.7625          | 0.7076   | 0.6676 | 0.7357    | 0.7090 |
+| 0.6821        | 0.1639 | 100  | 0.5465          | 0.7898   | 0.7818 | 0.7916    | 0.7905 |
+| 0.5475        | 0.2459 | 150  | 0.4972          | 0.8155   | 0.8074 | 0.8198    | 0.8161 |
+| 0.5397        | 0.3279 | 200  | 0.4992          | 0.8213   | 0.8168 | 0.8210    | 0.8217 |
+| 0.5328        | 0.4098 | 250  | 0.4999          | 0.8101   | 0.7988 | 0.8213    | 0.8109 |
+| 0.5052        | 0.4918 | 300  | 0.4983          | 0.8108   | 0.8131 | 0.8191    | 0.8107 |
+| 0.4627        | 0.5738 | 350  | 0.4597          | 0.8291   | 0.8290 | 0.8317    | 0.8291 |
+| 0.4565        | 0.6557 | 400  | 0.4328          | 0.8362   | 0.8332 | 0.8356    | 0.8366 |
+| 0.4187        | 0.7377 | 450  | 0.4416          | 0.8402   | 0.8361 | 0.8413    | 0.8406 |
+| 0.4611        | 0.8197 | 500  | 0.4655          | 0.8308   | 0.8306 | 0.8304    | 0.8311 |
+| 0.436         | 0.9016 | 550  | 0.4246          | 0.8335   | 0.8343 | 0.8350    | 0.8338 |
+| 0.4118        | 0.9836 | 600  | 0.4179          | 0.8429   | 0.8418 | 0.8425    | 0.8431 |
+| 0.4019        | 1.0656 | 650  | 0.4041          | 0.8436   | 0.8426 | 0.8426    | 0.8438 |
+| 0.419         | 1.1475 | 700  | 0.4238          | 0.8418   | 0.8405 | 0.8403    | 0.8422 |
+| 0.3656        | 1.2295 | 750  | 0.4046          | 0.8485   | 0.8486 | 0.8486    | 0.8487 |
+| 0.3559        | 1.3115 | 800  | 0.4032          | 0.8414   | 0.8415 | 0.8414    | 0.8417 |
+| 0.3529        | 1.3934 | 850  | 0.4229          | 0.8489   | 0.8452 | 0.8498    | 0.8494 |
+| 0.3247        | 1.4754 | 900  | 0.4198          | 0.8491   | 0.8463 | 0.8491    | 0.8494 |
+| 0.3435        | 1.5574 | 950  | 0.4254          | 0.8395   | 0.8413 | 0.8468    | 0.8394 |
+| 0.3519        | 1.6393 | 1000 | 0.4414          | 0.8447   | 0.8427 | 0.8472    | 0.8448 |
+| 0.3763        | 1.7213 | 1050 | 0.4097          | 0.8534   | 0.8521 | 0.8534    | 0.8536 |
+| 0.3739        | 1.8033 | 1100 | 0.3926          | 0.8523   | 0.8487 | 0.8540    | 0.8527 |
+| 0.3807        | 1.8852 | 1150 | 0.3896          | 0.8528   | 0.8515 | 0.8514    | 0.8531 |
+| 0.3655        | 1.9672 | 1200 | 0.3897          | 0.8526   | 0.8504 | 0.8535    | 0.8528 |
+| 0.3125        | 2.0492 | 1250 | 0.4199          | 0.8539   | 0.8540 | 0.8545    | 0.8540 |
+| 0.2851        | 2.1311 | 1300 | 0.4107          | 0.8550   | 0.8541 | 0.8554    | 0.8551 |
+| 0.2907        | 2.2131 | 1350 | 0.4093          | 0.8527   | 0.8532 | 0.8539    | 0.8528 |
+| 0.2619        | 2.2951 | 1400 | 0.4085          | 0.8585   | 0.8572 | 0.8573    | 0.8588 |
+| 0.2619        | 2.3770 | 1450 | 0.4166          | 0.8490   | 0.8501 | 0.8523    | 0.8491 |
+| 0.2863        | 2.4590 | 1500 | 0.4046          | 0.8548   | 0.8538 | 0.8536    | 0.8550 |
+| 0.2604        | 2.5410 | 1550 | 0.4143          | 0.8550   | 0.8544 | 0.8541    | 0.8552 |
+| 0.2778        | 2.6230 | 1600 | 0.4021          | 0.8532   | 0.8540 | 0.8551    | 0.8533 |
+| 0.2579        | 2.7049 | 1650 | 0.4071          | 0.8505   | 0.8518 | 0.8542    | 0.8505 |
+| 0.2734        | 2.7869 | 1700 | 0.4069          | 0.8565   | 0.8566 | 0.8567    | 0.8567 |
+| 0.2873        | 2.8689 | 1750 | 0.4006          | 0.8567   | 0.8563 | 0.8563    | 0.8569 |
+| 0.2568        | 2.9508 | 1800 | 0.3998          | 0.8567   | 0.8568 | 0.8570    | 0.8569 |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1+cu121
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "avichr/heBERT_sentiment_analysis",
+  "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": "Positive",
+    "1": "Neutral",
+    "2": "Negative"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Negative": 2,
+    "Neutral": 1,
+    "Positive": 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",
+  "total_flos": 6997313242916978688,
+  "transformers_version": "4.42.4",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

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