End of training

README.md

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+---
+library_name: transformers
+language:
+- spa
+license: mit
+base_model: diarizers-community/speaker-segmentation-fine-tuned-callhome-spa
+tags:
+- speaker-diarization
+- speaker-segmentation
+- generated_from_trainer
+datasets:
+- diarizers-community/callhome
+model-index:
+- name: speaker-segmentation-fine-tuned-callhome-spa
+  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. -->
+
+# speaker-segmentation-fine-tuned-callhome-spa
+
+This model is a fine-tuned version of [diarizers-community/speaker-segmentation-fine-tuned-callhome-spa](https://huggingface.co/diarizers-community/speaker-segmentation-fine-tuned-callhome-spa) on the diarizers-community/callhome dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3513
+- Der: 0.2029
+- False Alarm: 0.1480
+- Missed Detection: 0.0549
+- Confusion: 0.0000
+
+## 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: 0.001
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Der    | False Alarm | Missed Detection | Confusion |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
+| 0.3117        | 1.0   | 281  | 0.3448          | 0.2096 | 0.1526      | 0.0545           | 0.0024    |
+| 0.2973        | 2.0   | 562  | 0.3260          | 0.1961 | 0.1359      | 0.0601           | 0.0001    |
+| 0.2937        | 3.0   | 843  | 0.3413          | 0.2027 | 0.1468      | 0.0555           | 0.0004    |
+| 0.2953        | 4.0   | 1124 | 0.3466          | 0.2023 | 0.1467      | 0.0555           | 0.0000    |
+| 0.2725        | 5.0   | 1405 | 0.3513          | 0.2029 | 0.1480      | 0.0549           | 0.0000    |
+
+
+### Framework versions
+
+- Transformers 4.45.1
+- Pytorch 2.4.1
+- Datasets 3.0.1
+- Tokenizers 0.20.0

model.safetensors

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