End of training

.gitattributes

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+confusion_matrix_best.png filter=lfs diff=lfs merge=lfs -text
+confusion_matrix_latest.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,199 +1,92 @@
----
-library_name: transformers
-tags: []
----
-
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **Developed by:** [More Information Needed]
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-### Model Sources [optional]
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-## Uses
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-### Direct Use
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-## How to Get Started with the Model
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-Use the code below to get started with the model.
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-### Training Data
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-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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-#### Preprocessing [optional]
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-#### Training Hyperparameters
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-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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+---
+library_name: transformers
+tags:
+- generated_from_trainer
+datasets:
+- generator
+metrics:
+- accuracy
+- f1
+model-index:
+- name: EraClassifierBiLSTM
+  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. -->
+
+# EraClassifierBiLSTM
+
+This model is a fine-tuned version of [](https://huggingface.co/) on the generator dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0269
+- Accuracy: 0.6593
+- F1: 0.5103
+
+## 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: 0.0006535848403050624
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: reduce_lr_on_plateau
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Accuracy | F1     |
+|:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|
+| 1.1478        | 0.1031 | 2000  | 1.1945          | 0.5275   | 0.3487 |
+| 0.9699        | 0.2063 | 4000  | 1.0621          | 0.6357   | 0.4551 |
+| 0.9049        | 0.3094 | 6000  | 1.0657          | 0.5898   | 0.4074 |
+| 0.8577        | 0.4126 | 8000  | 1.0708          | 0.6032   | 0.4562 |
+| 0.8293        | 0.5157 | 10000 | 1.0425          | 0.6096   | 0.4274 |
+| 0.8002        | 0.6188 | 12000 | 1.0197          | 0.6157   | 0.4464 |
+| 0.7799        | 0.7220 | 14000 | 1.0540          | 0.6103   | 0.4576 |
+| 0.7545        | 0.8251 | 16000 | 1.0288          | 0.6266   | 0.4682 |
+| 0.7415        | 0.9283 | 18000 | 1.0332          | 0.6206   | 0.4614 |
+| 0.7205        | 1.0314 | 20000 | 1.0262          | 0.6333   | 0.4734 |
+| 0.7005        | 1.1345 | 22000 | 0.9989          | 0.6363   | 0.4840 |
+| 0.6924        | 1.2377 | 24000 | 1.0136          | 0.6347   | 0.4647 |
+| 0.6541        | 1.3408 | 26000 | 0.9917          | 0.6466   | 0.4951 |
+| 0.6261        | 1.4440 | 28000 | 0.9876          | 0.6465   | 0.4924 |
+| 0.6271        | 1.5471 | 30000 | 1.0057          | 0.6449   | 0.4976 |
+| 0.6124        | 1.6503 | 32000 | 0.9994          | 0.6494   | 0.5007 |
+| 0.6137        | 1.7534 | 34000 | 1.0015          | 0.6493   | 0.4976 |
+| 0.604         | 1.8565 | 36000 | 1.0058          | 0.6524   | 0.4997 |
+| 0.6063        | 1.9597 | 38000 | 1.0046          | 0.6512   | 0.5032 |
+| 0.5859        | 2.0628 | 40000 | 1.0162          | 0.6572   | 0.5121 |
+| 0.5778        | 2.1660 | 42000 | 1.0052          | 0.6591   | 0.5089 |
+| 0.5679        | 2.2691 | 44000 | 1.0288          | 0.6539   | 0.5044 |
+| 0.5646        | 2.3722 | 46000 | 1.0247          | 0.6559   | 0.5085 |
+| 0.5693        | 2.4754 | 48000 | 1.0250          | 0.6581   | 0.5096 |
+| 0.5607        | 2.5785 | 50000 | 1.0296          | 0.6573   | 0.5069 |
+| 0.5641        | 2.6817 | 52000 | 1.0266          | 0.6573   | 0.5080 |
+| 0.5601        | 2.7848 | 54000 | 1.0268          | 0.6577   | 0.5098 |
+| 0.5607        | 2.8879 | 56000 | 1.0263          | 0.6539   | 0.5060 |
+| 0.5582        | 2.9911 | 58000 | 1.0269          | 0.6593   | 0.5103 |
+
+
+### Framework versions
+
+- Transformers 4.49.0
+- Pytorch 2.6.0+cu126
+- Datasets 3.3.2
+- Tokenizers 0.21.0

final_model/config.json

@@ -0,0 +1,11 @@
+{
+  "architectures": [
+    "EraClassifierBiLSTM"
+  ],
+  "hidden_size": 2048,
+  "input_size": 8,
+  "num_eras": 6,
+  "num_layers": 2,
+  "torch_dtype": "float32",
+  "transformers_version": "4.49.0"
+}

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