End of training

README.md

@@ -1,5 +1,5 @@
 ---
-library_name: transformers
+library_name: peft
 license: mit
 base_model: FacebookAI/xlm-roberta-large
 tags:
@@ -13,29 +13,7 @@ metrics:
 - accuracy
 model-index:
 - name: finetuned_model
-  results:
-  - task:
-      name: Token Classification
-      type: token-classification
-    dataset:
-      name: biobert_json
-      type: biobert_json
-      config: Biobert_json
-      split: validation
-      args: Biobert_json
-    metrics:
-    - name: Precision
-      type: precision
-      value: 0.9387372613330209
-    - name: Recall
-      type: recall
-      value: 0.9591861160981449
-    - name: F1
-      type: f1
-      value: 0.9488515273502248
-    - name: Accuracy
-      type: accuracy
-      value: 0.9818015127206051
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -45,11 +23,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the biobert_json dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0725
-- Precision: 0.9387
-- Recall: 0.9592
-- F1: 0.9489
-- Accuracy: 0.9818
+- Loss: nan
+- Precision: 0.0025
+- Recall: 0.0130
+- F1: 0.0042
+- Accuracy: 0.0207
 
 ## Model description
 
@@ -69,26 +47,28 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
-- num_epochs: 3
-- mixed_precision_training: Native AMP
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.1161        | 1.0   | 612  | 0.0820          | 0.9354    | 0.9466 | 0.9410 | 0.9784   |
-| 0.08          | 2.0   | 1224 | 0.0764          | 0.9322    | 0.9563 | 0.9441 | 0.9803   |
-| 0.0547        | 3.0   | 1836 | 0.0725          | 0.9387    | 0.9592 | 0.9489 | 0.9818   |
+| 0.0           | 1.0   | 306  | nan             | 0.0025    | 0.0130 | 0.0042 | 0.0207   |
+| 0.0           | 2.0   | 612  | nan             | 0.0025    | 0.0130 | 0.0042 | 0.0207   |
+| 0.0           | 3.0   | 918  | nan             | 0.0025    | 0.0130 | 0.0042 | 0.0207   |
+| 0.0           | 4.0   | 1224 | nan             | 0.0025    | 0.0130 | 0.0042 | 0.0207   |
+| 0.0           | 5.0   | 1530 | nan             | 0.0025    | 0.0130 | 0.0042 | 0.0207   |
 
 
 ### Framework versions
 
+- PEFT 0.13.2
 - Transformers 4.46.3
 - Pytorch 2.5.1+cu121
 - Datasets 3.2.0
-- Tokenizers 0.20.3
+- Tokenizers 0.20.3