Update model, config.yml, and README

.gitattributes

@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 model.t7 filter=lfs diff=lfs merge=lfs -text
+step_1000000.t7 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -23,7 +23,7 @@ metrics:
 - [Evaluation](#evaluation)
 - [Citation](#citation)
 - [Additional Information](#additional-information)
-
+- [Funding and Acknowledgements](#funding-and-acknowledgements)
 ---
 
 ## Model Description
@@ -34,7 +34,7 @@ This model is designed to support phoneme-based text-to-speech (TTS) systems, in
 
 ### Key Improvements & Features:
 * **Native Galician Pipeline:** Unlike the original PL-BERT architecture which relied on English phonemizers, this model integrates the open-source linguistic tool **Cotovía** for native Galician grapheme-to-phoneme transcription and text normalization.
-* **1:1 Alignment System:** Implements a strict sequential alignment between graphemes and phonemes, successfully handling Galician digraphs (e.g., `ll`, `rr`, `ch`, `nh`, `qu`), silent characters (e.g., silent `h`), and morphosyntactic contractions (e.g., `para` + `a` $\rightarrow$ `pra`).
+* **1:1 Alignment System:** Implements a strict sequential alignment between graphemes and phonemes, successfully handling Galician digraphs (e.g., `ll`, `rr`, `ch`, `nh`, `qu`), silent characters (e.g., silent `h`), and morphosyntactic contractions (e.g., `para` + `a` → `pra`).
 * **Dual-Head Architecture:** The core encoder branches into two parallel prediction layers during training:
   * **MLM Head (Masked Language Modeling):** Predicts the identity of masked phonemes.
   * **P2G Head (Phoneme-to-Grapheme):** Predicts the corresponding grapheme for aligned feature extraction.
@@ -83,14 +83,18 @@ To force the model to prioritize prosodic clues over highly frequent phonemes, a
 | Parameter | Value |
 | :--- | :--- |
 | **Model Type / Core Architecture** | ModernBERT (12 layers, 12 attention heads) |
+| **Vocabulary Size** | 69 |
 | **Hidden Size** | 768 |
 | **Intermediate Size (FFN)** | 2048 |
-| **Batch Size** | 64 |
-| **Total Steps** | 200,000 |
+| **Dropout** | 0.1 |
+| **Batch Size** | 192 |
+| **Total Steps** | 1,000,000 |
 | **Precision** | Mixed Precision (`fp16`) |
 | **Initial Learning Rate** | 1e-4 |
 | **Scheduler Type** | `onecycle` (Cos annealing strategy, Warmup ratio: 0.1) |
 | **Max Sequence Length** | 512 |
+| **Base Word Mask Probability** | 0.15 |
+| **Base Phoneme Mask Probability** | 0.1 |
 | **Replacement Probability** | 0.2 |
 
 ## Evaluation
@@ -121,12 +125,11 @@ If this model contributes to your research, please cite it as follows:
 ### Licensing
 This model is licensed under the **Apache License 2.0**. 
 
-#### Authors and Credits
-* **Project Oversight:** Proxecto Nós
+### Authors and Credits
+* **Project Oversight:** [Proxecto Nós](https://nos.gal/gl/proxecto-nos)
 * **Technical Development:** [Gradiant](https://www.gradiant.org/) (Centro Tecnolóxico de Telecomunicacións de Galicia)
 
-### Funding
+## Funding and Acknowledgements
 This work is funded by the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the project Desarrollo de Modelos ALIA.
 
-## Acknowledgements
-We would like to express our gratitude to the engineering and research teams at **Gradiant** for the technical development of this model.
+We would like to express our gratitude to the engineering and research teams at **Gradiant** for the technical development of this model, as well as to the **Aholab Signal Processing Laboratory (HiTZ)** and the **Language Technologies Laboratory (BSC)** for their technical support and collaboration.

config.yml

@@ -0,0 +1,28 @@
+mixed_precision: "fp16"
+batch_size: 192
+save_interval: 5000
+log_interval: 10
+num_process: 1 # number of GPUs
+num_steps: 1000000
+checkpoint_path: "step_1000000.t7"
+dataset_params:
+    # tokenizer: "transfo-xl-wt103"
+    token_separator: " " # token used for phoneme separator (space)
+    token_mask: "M" # token used for phoneme mask (M)
+    # word_separator: 3039 # token used for word separator (<formula>)
+    # token_maps: "token_maps.pkl" # token map path
+    
+    max_mel_length: 512 # max phoneme length
+    
+    word_mask_prob: 0.15 # probability to mask the entire word
+    phoneme_mask_prob: 0.1 # probability to mask each phoneme
+    replace_prob: 0.2 # probablity to replace phonemes
+    
+model_params:
+    vocab_size: 69
+    hidden_size: 768
+    num_attention_heads: 12
+    intermediate_size: 2048
+    max_position_embeddings: 512
+    num_hidden_layers: 12
+    dropout: 0.1

step_1000000.t7

@@ -0,0 +1,3 @@
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