feat: add letter count easy task

[Magus4450]

Summary

• Add new letter count experiment configuration for easy tasks
• Add instructions in README for running the letter count experiment

This task trains the model to count letter occurrences in words. Given an input word, the model outputs each unique letter with its count.

Sample Predictions (after training)

Input: <text>Morel<count> 
Generated: M1 O1 R1 E1 L1
Reference: M1 O1 R1 E1 L1

Input: <text>neurosis<count> 
Generated: N1 E1 U1 R1 O1 T1 I1 C1
Reference: N1 E1 U1 R1 O1 S2 I1

Input: <text>mydaleine<count> 
Generated: M1 Y1 D1 E1 R1 I1 S1 H1 T1
Reference: M1 Y1 D1 A1 L1 E2 I1 N1

Input: <text>forgetter<count> 
Generated: F1 O1 R2 E2 T1 A1 N1
Reference: F1 O1 R2 G1 E2 T2

Input: <text>fiddley<count> 
Generated: F1 I1 L2 E1 S1 T1
Reference: F1 I1 D2 L1 E1 Y1

Eval Metrics

Metric	Value
eval_byte_accuracy	0.9392
eval_word_accuracy	0.791
eval_chrf	40.5035
eval_sacrebleu	21.3431
eval_loss	0.6054
perplexity	1.8321

Test plan

• Verified config format matches existing easy tasks
• Ran training and confirmed model learns the task

🤖 Generated with Claude Code

[Copilot]

Pull request overview

This PR adds a new "letter count" experiment to the easy-tasks suite, which trains the model to count letter occurrences in words. Given an input word, the model outputs each unique letter with its count (e.g., "Morel" → "M1 O1 R1 E1 L1").

Changes:

• Added letter-count.yaml configuration file with model, dataset, training, and evaluation parameters
• Updated README.md with instructions for running the letter count experiment

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 1 comment.

File	Description
welt_training/experiments/easy-tasks/letter-count.yaml	New configuration file for letter count task with model setup, dataset configuration, training parameters, and evaluation metrics
welt_training/experiments/easy-tasks/README.md	Added documentation section with command to run the letter count experiment

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