End of training

README.md

@@ -1,199 +1,82 @@
 ---
 library_name: transformers
-tags: []
+base_model: dccuchile/bert-base-spanish-wwm-uncased
+tags:
+- generated_from_trainer
+model-index:
+- name: Bert_TPF_v10
+  results: []
 ---
 
-# Model Card for Model ID
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-<!-- Provide a quick summary of what the model is/does. -->
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-## Model Details
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-### Model Description
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-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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+<!-- 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. -->
+
+# Bert_TPF_v10
+
+This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Accuracy@en: 0.8315
+- F1@en: 0.8323
+- Precision@en: 0.8373
+- Recall@en: 0.8368
+- Loss@en: 0.6173
+- Loss: 0.6173
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step  | Accuracy@en | F1@en  | Precision@en | Recall@en | Loss@en | Validation Loss |
+|:-------------:|:-----:|:-----:|:-----------:|:------:|:------------:|:---------:|:-------:|:---------------:|
+| 3.2405        | 1.0   | 552   | 0.2037      | 0.1306 | 0.1465       | 0.2065    | 2.5934  | 2.5934          |
+| 2.3891        | 2.0   | 1104  | 0.2992      | 0.2349 | 0.2586       | 0.3058    | 2.0876  | 2.0876          |
+| 2.0117        | 3.0   | 1656  | 0.3765      | 0.3448 | 0.3683       | 0.3839    | 1.8638  | 1.8638          |
+| 1.7804        | 4.0   | 2208  | 0.4619      | 0.4287 | 0.4433       | 0.4705    | 1.6337  | 1.6337          |
+| 1.4913        | 5.0   | 2760  | 0.5228      | 0.4905 | 0.5357       | 0.5306    | 1.3950  | 1.3950          |
+| 1.2177        | 6.0   | 3312  | 0.5696      | 0.5529 | 0.6054       | 0.5773    | 1.2562  | 1.2562          |
+| 1.0274        | 7.0   | 3864  | 0.6278      | 0.6086 | 0.6598       | 0.6360    | 1.0466  | 1.0466          |
+| 0.8372        | 8.0   | 4416  | 0.7050      | 0.7007 | 0.7254       | 0.7104    | 0.8734  | 0.8734          |
+| 0.67          | 9.0   | 4968  | 0.7407      | 0.7373 | 0.7510       | 0.7463    | 0.8112  | 0.8112          |
+| 0.5259        | 10.0  | 5520  | 0.8         | 0.7999 | 0.8069       | 0.8050    | 0.6594  | 0.6594          |
+| 0.4333        | 11.0  | 6072  | 0.8095      | 0.8056 | 0.8219       | 0.8159    | 0.6305  | 0.6305          |
+| 0.3503        | 12.0  | 6624  | 0.8019      | 0.7985 | 0.8132       | 0.8074    | 0.6698  | 0.6698          |
+| 0.2961        | 13.0  | 7176  | 0.8315      | 0.8323 | 0.8373       | 0.8368    | 0.6173  | 0.6173          |
+| 0.2441        | 14.0  | 7728  | 0.8450      | 0.8459 | 0.8482       | 0.8493    | 0.6287  | 0.6287          |
+| 0.2078        | 15.0  | 8280  | 0.8471      | 0.8477 | 0.8508       | 0.8511    | 0.6280  | 0.6280          |
+| 0.1857        | 16.0  | 8832  | 0.8463      | 0.8470 | 0.8513       | 0.8510    | 0.6293  | 0.6293          |
+| 0.164         | 17.0  | 9384  | 0.8471      | 0.8480 | 0.8510       | 0.8512    | 0.6371  | 0.6371          |
+| 0.1467        | 18.0  | 9936  | 0.8489      | 0.8497 | 0.8536       | 0.8532    | 0.6410  | 0.6410          |
+| 0.1409        | 19.0  | 10488 | 0.8489      | 0.8496 | 0.8535       | 0.8528    | 0.6396  | 0.6396          |
+| 0.1378        | 20.0  | 11040 | 0.8497      | 0.8505 | 0.8543       | 0.8537    | 0.6395  | 0.6395          |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.5.0+cu121
+- Datasets 3.0.2
+- Tokenizers 0.19.1

all_results.json

@@ -0,0 +1,17 @@
+{
+    "epoch": 20.0,
+    "eval_accuracy@en": 0.8314814814814815,
+    "eval_f1@en": 0.8323234021579463,
+    "eval_loss": 0.6172820329666138,
+    "eval_loss@en": 0.6172820329666138,
+    "eval_precision@en": 0.8373285994054867,
+    "eval_recall@en": 0.8367783650241256,
+    "eval_runtime": 107.5607,
+    "eval_samples_per_second": 35.143,
+    "eval_steps_per_second": 2.203,
+    "total_flos": 4.6429459034112e+16,
+    "train_loss": 0.8748937793399977,
+    "train_runtime": 23732.1257,
+    "train_samples_per_second": 7.433,
+    "train_steps_per_second": 0.465
+}

eval_results.json

@@ -0,0 +1,12 @@
+{
+    "epoch": 20.0,
+    "eval_accuracy@en": 0.8314814814814815,
+    "eval_f1@en": 0.8323234021579463,
+    "eval_loss": 0.6172820329666138,
+    "eval_loss@en": 0.6172820329666138,
+    "eval_precision@en": 0.8373285994054867,
+    "eval_recall@en": 0.8367783650241256,
+    "eval_runtime": 107.5607,
+    "eval_samples_per_second": 35.143,
+    "eval_steps_per_second": 2.203
+}

train_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 20.0,
+    "total_flos": 4.6429459034112e+16,
+    "train_loss": 0.8748937793399977,
+    "train_runtime": 23732.1257,
+    "train_samples_per_second": 7.433,
+    "train_steps_per_second": 0.465
+}

training_args.bin

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