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stulcrad
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CNEC1_1_extended_xlm-roberta-large

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xlm-roberta
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End of training

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Files changed (4) hide show
  1. README.md +19 -24
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -25,16 +25,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.8641078838174274
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  - name: Recall
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  type: recall
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- value: 0.8904329235702833
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  - name: F1
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  type: f1
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- value: 0.877072913924717
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  - name: Accuracy
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  type: accuracy
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- value: 0.970074812967581
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the cnec dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1937
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- - Precision: 0.8641
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- - Recall: 0.8904
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- - F1: 0.8771
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- - Accuracy: 0.9701
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  ## Model description
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@@ -68,27 +68,22 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 4
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- - eval_batch_size: 4
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 10
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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- |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.3037 | 1.0 | 1161 | 0.1876 | 0.7785 | 0.8113 | 0.7946 | 0.9529 |
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- | 0.2331 | 2.0 | 2322 | 0.2008 | 0.8065 | 0.8263 | 0.8163 | 0.9569 |
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- | 0.1828 | 3.0 | 3483 | 0.1656 | 0.8332 | 0.8648 | 0.8487 | 0.9648 |
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- | 0.1456 | 4.0 | 4644 | 0.1659 | 0.8414 | 0.8675 | 0.8542 | 0.9643 |
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- | 0.1237 | 5.0 | 5805 | 0.1746 | 0.8538 | 0.8899 | 0.8715 | 0.9690 |
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- | 0.1074 | 6.0 | 6966 | 0.1782 | 0.8584 | 0.8878 | 0.8728 | 0.9691 |
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- | 0.097 | 7.0 | 8127 | 0.1802 | 0.8517 | 0.8840 | 0.8676 | 0.9691 |
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- | 0.072 | 8.0 | 9288 | 0.1908 | 0.8636 | 0.8867 | 0.875 | 0.9703 |
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- | 0.067 | 9.0 | 10449 | 0.1962 | 0.8672 | 0.8936 | 0.8802 | 0.9711 |
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- | 0.0636 | 10.0 | 11610 | 0.1937 | 0.8641 | 0.8904 | 0.8771 | 0.9701 |
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  ### Framework versions
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.8533541341653667
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  - name: Recall
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  type: recall
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+ value: 0.8770710849812934
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  - name: F1
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  type: f1
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+ value: 0.8650500790722193
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9670664608320468
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the cnec dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1498
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+ - Precision: 0.8534
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+ - Recall: 0.8771
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+ - F1: 0.8651
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+ - Accuracy: 0.9671
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 5
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.3961 | 1.0 | 581 | 0.1800 | 0.8004 | 0.8231 | 0.8116 | 0.9560 |
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+ | 0.1772 | 2.0 | 1162 | 0.1518 | 0.8357 | 0.8648 | 0.8500 | 0.9642 |
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+ | 0.1266 | 3.0 | 1743 | 0.1545 | 0.8377 | 0.8717 | 0.8544 | 0.9680 |
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+ | 0.1043 | 4.0 | 2324 | 0.1472 | 0.8473 | 0.8691 | 0.8580 | 0.9656 |
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+ | 0.0804 | 5.0 | 2905 | 0.1498 | 0.8534 | 0.8771 | 0.8651 | 0.9671 |
 
 
 
 
 
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  ### Framework versions
config.json CHANGED
@@ -8,7 +8,7 @@
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  "eos_token_id": 2,
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  "classifier_dropout": null,
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  "eos_token_id": 2,
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  "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.2,
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  "hidden_size": 1024,
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  "id2label": {
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  "0": "O",
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