Model save

README.md

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+---
+base_model: bigcode/starencoder
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- accuracy
+model-index:
+- name: stack-edu-classifier-javascript
+  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. -->
+
+# stack-edu-classifier-javascript
+
+This model is a fine-tuned version of [bigcode/starencoder](https://huggingface.co/bigcode/starencoder) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3612
+- Precision: 0.5135
+- Recall: 0.3322
+- F1 Macro: 0.3711
+- Accuracy: 0.6277
+- F1 Binary Minimum3: 0.5704
+
+## 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: 0.0003
+- train_batch_size: 64
+- eval_batch_size: 256
+- seed: 0
+- distributed_type: multi-GPU
+- num_devices: 2
+- total_train_batch_size: 128
+- total_eval_batch_size: 512
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 200
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch   | Step  | Validation Loss | Precision | Recall | F1 Macro | Accuracy | F1 Binary Minimum3 |
+|:-------------:|:-------:|:-----:|:---------------:|:---------:|:------:|:--------:|:--------:|:------------------:|
+| No log        | 0       | 0     | 5.6298          | 0.0010    | 0.1667 | 0.0020   | 0.0059   | 0                  |
+| 0.3853        | 1.4493  | 1000  | 0.3886          | 0.4945    | 0.3110 | 0.3354   | 0.6037   | 0.5761             |
+| 0.3791        | 2.8986  | 2000  | 0.3729          | 0.5041    | 0.3090 | 0.3395   | 0.6208   | 0.5716             |
+| 0.3722        | 4.3478  | 3000  | 0.3720          | 0.5261    | 0.3116 | 0.3440   | 0.6189   | 0.5673             |
+| 0.3751        | 5.7971  | 4000  | 0.3704          | 0.5247    | 0.3204 | 0.3565   | 0.6199   | 0.5766             |
+| 0.3651        | 7.2464  | 5000  | 0.3718          | 0.5113    | 0.3352 | 0.3678   | 0.6310   | 0.5161             |
+| 0.3695        | 8.6957  | 6000  | 0.3649          | 0.5055    | 0.3253 | 0.3607   | 0.6249   | 0.5632             |
+| 0.361         | 10.1449 | 7000  | 0.3647          | 0.5042    | 0.3236 | 0.3571   | 0.6354   | 0.5410             |
+| 0.3666        | 11.5942 | 8000  | 0.3764          | 0.5290    | 0.3371 | 0.3752   | 0.6146   | 0.5941             |
+| 0.3563        | 13.0435 | 9000  | 0.3617          | 0.5179    | 0.3356 | 0.3743   | 0.6303   | 0.5674             |
+| 0.3735        | 14.4928 | 10000 | 0.3663          | 0.4998    | 0.3423 | 0.3760   | 0.6340   | 0.5320             |
+| 0.349         | 15.9420 | 11000 | 0.3616          | 0.5063    | 0.3306 | 0.3681   | 0.6273   | 0.5696             |
+| 0.3679        | 17.3913 | 12000 | 0.3632          | 0.5078    | 0.3396 | 0.3786   | 0.6252   | 0.5762             |
+| 0.3622        | 18.8406 | 13000 | 0.3612          | 0.5135    | 0.3322 | 0.3711   | 0.6277   | 0.5704             |
+
+
+### Framework versions
+
+- Transformers 4.43.4
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

final/config.json

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+{
+  "_name_or_path": "bigcode/starencoder",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": 0.0,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
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+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
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+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 1024,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 49152,
+  "position_embedding_type": "absolute",
+  "problem_type": "regression",
+  "torch_dtype": "float32",
+  "transformers_version": "4.43.4",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 49156
+}

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